SEMICONDUCTOR PACKAGE INSPECTION METHOD AND METHOD OF MANUFACTURING SEMICONDUCTOR DEVICE BY USING THE SAME

§103 §112

DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Response to Amendment The Amendment filed 20 July 2026 has been entered. Claims 1-20 remain pending in the application. Applicant’s amendments to Claims 1-20 have overcome each and every objection and U.S.C. 112 claim interpretation previously set forth in the Non-Final Office Action mailed on 27 April 2026. However, Applicant’s amendments to Claims 1-20 do not overcome the U.S.C. 112 rejections nor the U.S.C. 103 rejections. Response to Arguments Applicant’s arguments, see Remarks, filed 20 July 2026, with respect to the U.S.C. 103 rejections of claims 1-20 have been considered but are moot because the new ground of rejection has newly cited references teaching the amended claim. Claim Objections Claims 9 and 17 are objected to because of the following informalities: In claim 9 line 2, “the at least the portion” should be corrected to say –at least the portion—. In claim 17 line 2, “the at least the portion” should be corrected to say –at least the portion—. Appropriate correction is required. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. In claims 1, 11 and 19, “at least a portion of” is unclear because under broadest reasonable interpretation, a portion can be considered any percentage including 0% or 100%. Specification para. [0007]-[0009], [0047]-[0049], [0056], [0083], [0086], [0089] merely uses the same language “at least a portion of” and does not specify the definition or range of “at least a portion of”. For examination purposes, “at least a portion of” is interpreted to mean “a portion of” which can be any percentage including 0% or 100%. Examiner recommends further limiting the term “portion of” Claims 2-10, 12-18 and 20 are rejected due to their dependencies. Claim Rejections - 35 USC § 103 The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claims 1 and 7-10 are rejected under 35 U.S.C. 103 as being unpatentable over Pavani (US 20160123897 A1 in view of Kondo et al. (US20150354947), hereinafter Kondo. As to claim 1, Pavani teaches an inspection method (Pavani [0001]; “wafer image processing for use in wafer inspection”) comprising: providing a semiconductor package including a surface (Pavani [0022]; fig. 1; “surface 1 is a semiconductor wafer”), the surface including a plurality of segments (Pavani [0035]; fig. 5; pixel regions 8A, 8B, 8C, 8D); obtaining a plurality of vision images by using light from a plurality of illuminations (Pavani [0028]-[0029]; fig. 5; “In block 17, images of feature are acquired… In block 23, images of surface are acquired”. Thus, there is a plurality of illuminations to acquire the plurality of images in fig. 5), wherein the plurality of illuminations are disposed at first positions corresponding to a first set of latitudes and longitudes (Pavani fig. 5; [0035]; the image 5 is of the surface with a grid indicating a set of latitudes and longitudes; and the images 9, 11, 13, 15 are of the features each with a grid indicating a set of latitudes and longitudes); obtaining a bidirectional reflectance distribution function (BRDF) of the surface by using the plurality of vision images (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”); rendering the plurality of vision images by using the BRDF (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”. Thus, a plurality of vision images is rendered using BRDF) to obtain a rendered image (Pavani fig. 3; the surface scattering model 22B) including an image information obtained by using virtual light (Pavani [0029]; “In block 22B, a scattering model is computed from the structural model of surface… Scattering model comprises information on scattered radiation in a plurality of polar and azimuthal angles. The scattered radiation is generated by scattering of an electromagnetic radiation by the surface” (emphasis added). Thus, the surface scattering model includes information obtained by using this computed model, i.e. this virtual model of scattered light), wherein the virtual light is disposed at second positions corresponding to a second set of latitudes and longitudes, and the first set of latitudes and longitudes is different from the second set of latitudes and longitudes (Pavani [0033]; claim 5; “wherein said computing a scattering model comprises: discretizing said structural model into a plurality of points located on a grid”, which is a computed scattered model grid, separate from the fig. 5 grid indicating the first set of latitudes and longitudes with “multiple points” (Pavani claim 1)), and performing a two-dimensional (2D) Fourier transform (Pavani [0029]-[0030]; fig. 3; “ In some embodiments, the scattering of surface is modeled by computing a Fourier Transformation of the structural model of surface… In block 24, a filter is designed based on the scattering model of feature and scattering model of surface to achieve a predetermined filter performance metric… Consider F(θ,φ) to be the scattering model of feature, where θ is the polar angle and φ is the azimuthal angle. Similarly, consider S(θ,φ) to be the scattering model of surface. Both F and S are complex electromagnetic fields having an intensity and phase value at each θ and φ”. Thus, the Fourier transform is two-dimensional: θ and φ) on a first synthesis image of the rendered image (Pavani [0029]; structural model) and at least a portion of the plurality of vision images to obtain a power spectrum density (PSD) of the surface (Pavani [0029]; “A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”). Pavani para. [0029] teaches; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter”. In the same paragraph, Pavani also teaches; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed. Further, an autocorrelation of surface profile is computed. A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated. A total integrated scatter is calculated from the ensemble roughness metric, correlation length, angle of incidence of electromagnetic beam, and wavelength of electromagnetic radiation”. However, Pavani does not explicitly disclose selecting a spatial-frequency interval of the PSD; quantifying roughness of the surface by performing an integral on the PSD over the spatial-frequency interval; and wherein the virtual light is from a plurality of virtual illuminations disposed at the second positions. Kondo, in the same field of endeavor as the claimed invention, teaches selecting a spatial-frequency interval of the PSD; and quantifying roughness of the surface by performing an integral on the PSD over the spatial-frequency interval (Kondo [0037]; “First, the PSD function will be described. When a surface shape is expressed using three-dimensional coordinates (X, Y, Z), a height Z may be two-dimensionally Fourier transformed with respect to (X, Y), and a value obtained by squaring amplitude thereof may be expressed as a spatial frequency spectrum. The spatial frequency spectrum becomes a function P(fx, fy) in which (fx, fy) which are reciprocals of (X, Y) are used as variables. P(fr) obtained by expressing the function P using fr=°(fx×fx+fy×fy) indicates a power spectral density (PSD) function. The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include selecting a spatial-frequency interval of the PSD; and quantifying roughness of the surface by performing an integral on the PSD over the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitation such as wherein the virtual light is from a plurality of virtual illuminations disposed at the second positions. However, applicant has not provided criticality for wherein the virtual light is from a plurality of virtual illuminations disposed at the second positions. Applicant discloses merely that “the virtual light is from a plurality of virtual illuminations disposed at second positions” (Specification para. [0007]-[0008], [0068]) and “an arbitrary light irradiation direction of each of the virtual illuminations may be set” (specification para. [0068] and [0071]). Pavani in view of Kondo shows that the virtual light is disposed at second positions corresponding to a second set of latitudes and longitudes; creating the computed scattering model with a plurality of points on a grid (Pavani claim 5). Thus, the virtual light has different light irradiation directions allowing for the plurality of points on the grid. Further, a mere change in size or design choice of a component is generally recognized as being within the level of ordinary skill in the art. In re Rose, 105 USPQ 237 (CCPA 1955). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate wherein the virtual light is from a plurality of virtual illuminations disposed at the second positions for the advantage of more precise virtual modeling. PNG media_image1.png 554 749 media_image1.png Greyscale Pavani Fig. 1 PNG media_image2.png 1285 724 media_image2.png Greyscale Pavani Fig. 3 PNG media_image3.png 486 991 media_image3.png Greyscale Pavani Fig. 5 As to claim 7, Pavani teaches the inspection method of claim 1, further comprising: determining a measurement target of the roughness (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed” (emphasis added)); and selecting the at least the portion of the plurality of vision images based on the latitude of each of the plurality of illuminations and the measurement target (Pavani fig. 5; [0035]; The images 9, 11, 13, 15 are of the features of the targeted pixel regions 8A, 8B, 8C, 8D each with a grid of latitudes and longitudes. Thus, there is a plurality of illuminations to acquire the plurality of images in fig. 5). As to claim 8, Pavani teaches the inspection method of claim 7, wherein: the measurement target is a width (Pavani [0029]; “A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated”). Pavani does not explicitly disclose the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, and each of the first latitudes has a value between -15 degrees and 15 degrees. However, Applicant has not provided criticality for the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, and each of the first latitudes has a value between -15 degrees and 15 degrees. Specification para. [0048] merely states “In an embodiment, when the measurement target is a width, the at least portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at a first latitudes. Each of the first latitudes may have a value between about -15 degrees and about 15 degrees”. Further, it has been held that finding the optimal or working ranges of a variable involves only routine skill in the art (MPEP 2144.05). In re Aller, 105 USPQ 233. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980). Peterson, 315 F.3d at 1330, 65 USPQ2d at 1382. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, and each of the first latitudes has a value between -15 degrees and 15 degrees; for the advantage of enhanced design precision (Pavani [0023]). As to claim 9, Pavani teaches the inspection method of claim 7, wherein; the measurement target is a height (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed” (emphasis added). Pavani does not explicitly disclose the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, and each of the second latitudes has a value between -90 degrees and -75 degrees or between 75 degrees to 90 degrees. However, Applicant has not provided criticality for the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, and each of the second latitudes has a value between -90 degrees and -75 degrees or between 75 degrees to 90 degrees. Specification para. [0049] merely states “In an embodiment, when the measurement target is a height, the at least portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at a second latitudes. Each of the second latitudes may have a value between about -90 degrees and -75 degrees or between about 75 degrees to about 90 degrees”. Further, it has been held that finding the optimal or working ranges of a variable involves only routine skill in the art (MPEP 2144.05). In re Aller, 105 USPQ 233. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980). Peterson, 315 F.3d at 1330, 65 USPQ2d at 1382. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, and each of the second latitudes has a value between -90 degrees and -75 degrees or between 75 degrees to 90 degrees; for the advantage of enhanced design precision (Pavani [0023]). As to claim 10, Pavani teaches the inspection method of claim 7, wherein the performing of the integral on the PSD comprises: calculating an integral value of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added). “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency); setting an index value based on the measurement target (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed. Further, an autocorrelation of surface profile is computed. A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated. A total integrated scatter is calculated from the ensemble roughness metric, correlation length, angle of incidence of electromagnetic beam, and wavelength of electromagnetic radiation” (emphasis added). Thus, the total integrated scatter is set based on the ensemble roughness metric); and calculating a distribution of the integral value of the index value (Pavani [0029]; fig. 5; “A bidirectional reflection distribution function is used to calculate the scattering model of surface”. Thus, the bidirectional reflection distribution function is calculating of the total integrated scatter). However, Pavani does not explicitly disclose the integral value of the PSD of a spatial frequency in the spatial-frequency interval. Kondo, in the same field of endeavor as the claimed invention, teaches the integral value of the PSD of a spatial frequency in the spatial-frequency interval (Kondo [0047]; “Next, the procedure of calculating the surface roughness from the PSD function will be described... The RMS roughness becomes a value obtained by integrating a product of a PSD function 401 and a spatial, frequency f in a certain spatial frequency band (band f1 to f2 in FIG. 4). When an integration interval f1 to f2 is arbitrarily selected and the RMS roughness in the interval is set as RMS(f1, f2), RMS(f1, f2)=√(2π∫f2 f1PSD(f)×fdf)”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral value of the PSD of a spatial frequency in the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo, further in view of Hayashi et al. (US8433102B2), hereinafter Hayashi. As to claim 2, Pavani teaches the inspection method of claim 1, wherein the obtaining of the plurality of vision images comprises: preparing a light receiver configured to detect light information from the surface (Pavani fig. 1; [0022]; imaging module 4 collects scattered radiation from a wide area of surface 1); inputting wavelength and intensity information to the plurality of illuminations (Pavani [0026]; fig. 5; “From the intensities of pixels allocated for the lens, the phase gradient of scattered radiation incident on the lens is determined”. Thus, information of phase and intensity are received on the grids of the images in fig. 5, i.e. on the plurality of illuminations. Therefore, information of wavelength, the inverse of phase, and intensity is input to the grids of the images from the wafer surface 1), wherein the plurality of illuminations are arranged at latitudinal intervals along each longitude and at longitudinal intervals along each latitude (Pavani fig. 5; [0035]; The image 5 is of the surface with a grid indicating a set of latitudes and longitudes; and the images 9, 11, 13, 15 are of the features each with a grid indicating a set of latitudes and longitudes. The grids show the illuminations disposed by a repeating interval along both the longitudinal and latitudinal directions, thus, creating the grids); inputting power to the plurality of illuminations (Pavani [0030]; “In some embodiments, the predetermined performance metric comprises maximizing the ratio of scattered power from feature to scattered power from surface”. Thus, power is input to irradiate light onto the wafer surface); and obtaining the plurality of vision images by using a light receiver (Pavani [0028]-[0029]; fig. 5; “In block 17, images of feature are acquired… In block 23, images of surface are acquired”). However, Pavani in view of Kondo does not explicitly disclose the light receiver is a camera. Hayashi, in the same field of endeavor as the claimed invention, teaches the light receiver is a camera (Hayashi col. 4 ln. 44-48; CCD camera 20). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Hayashi to include the light receiver is a camera; for the advantage of effectively receiving light for roughness inspection (Hayashi col. 4 ln. 43-64). Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view Kondo, further in view of Hivet et al. (WO2021190986A1), hereinafter Hivet, and further in view of Dingeldey (US20200193695A1). As to claim 3, Pavani teaches the inspection method of claim 1, wherein the obtaining of the BRDF comprises: synthesizing the plurality of vision images (Pavani [0028]-[0029]; “In block 17, images of feature are acquired… In block 23, images of surface are acquired”. Thus, there is a plurality of illuminations to acquire the plurality of images) to obtain a second synthesis image (Pavani [0029]; scattering model); obtaining a reflection characteristic of each of the plurality of segments from the second synthesis image (Pavani [0029]; fig. 5; “a bidirectional reflection distribution function is used to calculate the scattering model of surface”, which defines how light is reflected off the surface, i.e. a reflection characteristic of each of the pixel regions 8A, 8B, 8C, 8D). However, Pavani in view of Kondo does not explicitly disclose calculating a reflection coefficient of a diffusive light component and a reflection coefficient of a specular light component from the reflection characteristic of each of the plurality of segments with respect to first set of latitudes and longitudes; and obtaining a three-dimensional (3D) shape information by using the reflection coefficient of the diffusive light component, the reflection coefficient of the specular light component and a normal vector of the reflection coefficient of each of the plurality of segments. Hivet, in the same field of endeavor as the claimed invention, teaches calculating a reflection coefficient of a diffusive light component and a reflection coefficient of a specular light component (Hivet [0014]; “combining the Lambertian BRDF and the specular BRDF”) from the reflection characteristic of each of the plurality of segments with respect to first set of latitudes and longitudes (Hivet fig. 2; [0033]-[0039]; [0046]; The calculation of Lambertian BRDF, that can be computer implemented, has a diffuse reflection coefficient dependent on λ wavelength and θ incident angle of the incident light on the face 1001a. Thus, different segments of the illuminations have different diffuse reflection coefficients); and obtaining a three-dimensional (3D) shape information by using the reflection coefficient of the diffusive light component and the reflection coefficient of the specular light component (Hivet abstract; [0014]; “allows to render accurately sheet of transparent glass comprising an opaque layer in a realistic way in a 3D virtual scene through the calculation of Lambertian bidirectional reflectance distribution function from diffuse reflection spectrum” by “combining the Lambertian BRDF and the specular BRDF”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Hivet to include calculating a reflection coefficient of a diffusive light component and a reflection coefficient of a specular light component from the reflection characteristic of each of the plurality of segments with respect to first set of latitudes and longitudes; and obtaining a three-dimensional (3D) shape information by using the reflection coefficient of the diffusive light component and the reflection coefficient of the specular light component; for the advantage of improving the rendering (Hivet [0014]). Still lacking the limitation such as obtaining a three-dimensional (3D) shape information by using a normal vector of the reflection coefficient of each of the plurality of segments. Dingeldey, in the same field of endeavor as the claimed invention, teaches obtaining the shape information by using a normal vector of the reflection coefficient of each of the plurality of segments (Dingeldey [0006]; [0063]-[0071]; “performing direct volume rendering of a volumetric dataset” by using a bi-directional reflection distribution function with an anisotropic illumination model dependent on N a normal vector at each sample point). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Hivet to incorporate the teachings of Dingeldey to include obtaining the shape information by using a normal vector of the reflection coefficient of each of the plurality of segments; for the advantage of defining the change when applying infinitesimal positional changes on the surface (Dingeldey [0144]). PNG media_image4.png 512 1095 media_image4.png Greyscale Hivet Fig. 2 Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo, Hivet and Dingeldey, further in view of Neulander et al. (US 20190311467 A1), hereinafter Neulander. As to claim 4, Pavani teaches the inspection method of claim 3. Pavani in view of Kondo does not explicitly disclose wherein the rendering of the plurality of vision images comprises: setting an arbitrary light irradiation direction of each of the plurality of virtual illuminations; and obtaining the rendered image by using the reflection coefficient of the diffusive light component of each of the plurality of segments, the reflection coefficient of the specular light component of each of the plurality of segments, the normal vector of the reflection coefficients, and a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments. However, applicant has not provided criticality for wherein the rendering of the plurality of vision images comprises: setting an arbitrary light irradiation direction of each of the plurality of virtual illuminations. Applicant discloses merely “setting an arbitrary light irradiation direction, with respect to a latitude θ and a longitude Φ where an illumination is not designated” (Specification para. [0068]) and “an arbitrary light irradiation direction (i.e., virtual illumination)” (Specification para. [0075]). Pavani in view of Kondo shows that the virtual light is disposed at second positions corresponding to a second set of latitudes and longitudes; creating the computed scattering model with a plurality of points on a grid (Pavani claim 5). Also, bidirectional reflectance distribution function utilizes different light irradiation directions. Thus, the virtual light has set an arbitrary light irradiation direction of each of the plurality of virtual illuminations. Further, a mere change in size or design choice of a component is generally recognized as being within the level of ordinary skill in the art. In re Rose, 105 USPQ 237 (CCPA 1955). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate wherein the rendering of the plurality of vision images comprises: setting an arbitrary light irradiation direction of each of the plurality of virtual illuminations; for the advantage of more precise virtual modeling. Still lacking the limitations such as obtaining the rendered image by using the reflection coefficient of the diffusive light component of each of the plurality of segments, the reflection coefficient of the specular light component of each of the plurality of segments, the normal vector of the reflection coefficients, and a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments. Hivet, in the same field of endeavor as the claimed invention, teaches obtaining the rendered image by using the reflection coefficient of the diffusive light component of each of the plurality of segments and the reflection coefficient of the specular light component (Hivet [0014]; “combining the Lambertian BRDF and the specular BRDF”) of each of the segments (Hivet fig. 2; [0033]-[0039]; [0046]; The calculation of Lambertian BRDF, that can be computer implemented, has a diffuse reflection coefficient dependent on λ wavelength and θ incident angle of the incident light on the face 1001a. Thus, different segments of the illuminations have different diffuse reflection coefficients). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Hivet to include obtaining the rendered image by using the reflection coefficient of the diffusive light component of each of the plurality of segments and the reflection coefficient of the specular light component of each of the segments; for the advantage of improving the rendering (Hivet [0014]). Still lacking the limitation such as obtaining a rendered image by using the normal vector of the reflection coefficients and a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments. Dingeldey, in the same field of endeavor as the claimed invention, teaches obtaining a rendered image by using the normal vector of the reflection coefficients (Dingeldey [0006]; [0063]-[0071]; “performing direct volume rendering of a volumetric dataset” by using a bi-directional reflection distribution function with an anisotropic illumination model dependent on N a normal vector at each sample point). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Hivet to incorporate the teachings of Dingeldey to include obtaining a rendered image by using the normal vector of the reflection coefficients; for the advantage of defining the change when applying infinitesimal positional changes on the surface (Dingeldey [0144]). Still lacking the limitation such as obtaining a rendered image by using a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments. Neulander, in the same field of endeavor as the claimed invention, teaches obtaining a rendered image by using a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments (Neulander [0020]; “The accurate rendering of specular reflections requires knowledge of incoming light from all directions in the surrounding environment at high angular resolution… the specular reflection may be split or partitioned into two components (e.g., at least two components), an environment map component and a camera feed component. The two components are then blended (e.g., combined) based on a function of an angle between a negated view vector (e.g., a vector in a direction opposite to a view vector) and a surface normal vector” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo, Hivet and Dingeldey to incorporate the teachings of Neulander to include obtaining a rendered image by using a reverse direction vector of the arbitrary light irradiation direction of each of the plurality of virtual illuminations with respect to each of the plurality of segments; for the advantage of enhanced rendering accuracy (Neulander [0020]). Claims 5-6 are rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo, further in view of Lavoie et al. (US 20240312016 A1), hereinafter Lavoie. As to claim 5, Pavani teaches the inspection method of claim 1, wherein the selecting of the integral section of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added)) comprises: changing the PSD to a PSD function, wherein the PSD is a function of a spatial frequency (Pavani [0029]; “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency); and setting a range including at least a portion of the plurality of PSD points to the integral section (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter”. [0031]; “A(θ,φ) comprises information on the range of scattering angles collected by the imaging module” (emphasis added)). However, Pavani does not explicitly disclose the integral section is the spatial-frequency interval; performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function, wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Kondo, in the same field of endeavor as the claimed invention, teaches the integral section is the spatial-frequency interval (Kondo [0037]; The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral section is the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitations such as performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function, wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Lavoie, in the same field of endeavor as the claimed invention, teaches performing a differentiation of the PSD on the spatial frequency (Lavoie abstract; “local spatial orientation and frequency variation”) by using the PSD function (Lavoie [0065]; “The radial spectral power density is used to determine fractional power in at least one vessel segment”. [0153]; “In some embodiments, the segmentation technique described herein” uses “partial differential equation-based methods”. Thus, the partial differential of the PSD of the PSD on the spatial frequency can be performed); setting a threshold value (Lavoie claim 1; “(b) comparing the image quality pattern obtained in (a) with a predefined image quality threshold pattern, wherein the quality threshold pattern comprises at least one threshold”); selecting a plurality of PSD points in a graph of the PSD function (Lavoie [0198]; “The term “angular spectral power density”, as used herein, refers to the angularly (over a certain range of orientation, for 0 to 180 degrees) average value of the spectral power density. Therefore, the angular spectral power can represent the density distribution of the power spectral density as a function of angle or orientation, over the range 0 to 180 degrees, in the image” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Lavoie to include performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Further, Pavani in view of Kondo and Lavoie teach using the PSD function (Lavoie [0197]-[0198]). A person of ordinary skill would have readily employed known computational analyses to quantify the absolute values of slopes at each of the plurality of PSD points, and compare them to a threshold value. Given Pavani in view of Lavoie’s explicit encouragement of computing a power spectral density function and comparing the image quality pattern with a predefined image quality threshold pattern (Lavoie claim 1), measuring the power spectral density graph and correlating the absolute value of the slopes to the threshold would have been an obvious and predictable modification. Still lacking the limitation such as wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. However, Applicant has not provided criticality for wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Specification para. [0084] merely states “FIG. 7B is a graph showing a correlation of a slope absolute value of a power energy spectrum density with respect to a space frequency, according to an embodiment”. Specification para. [0086] merely states “In an embodiment, when a threshold value is set to 10, PSD points at which the absolute value f'q of the slope of the PSD is greater than or equal to the threshold value may correspond to PSD points denoted by circles in the graph of FIG. 7B”. Furthermore, intended use and other types of functional language must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable to performing the intended use, and then it meets the claim. It has been held that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations. Ex Parte Masham, 2 USPQ F.2d 1647 (1987). In a claim drawn to a process to making, the intended use must result in a manipulative difference as compared to the prior art. In Regarding claim Casey, 152 USPQ 235 (CCPA 1967); In Regarding claim Otto, 136 USPQ 458, 459 (CCPA 1963). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Lavoie to incorporate wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). As to claim 6, Pavani teaches the inspection method of claim 1, wherein the selecting of the integral section of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added)) comprises: changing the PSD to a PSD function, wherein the PSD is a function of a spatial frequency (Pavani [0029]; “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency). However, Pavani does not explicitly disclose the integral section is the spatial-frequency interval; performing a differentiation of the PSD on the spatial frequency by using the PSD function; calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; and setting a range including at least portion of the upper 25% values as the spatial-frequency interval. Kondo, in the same field of endeavor as the claimed invention, teaches the integral section is the spatial-frequency interval (Kondo [0037]; The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral section is the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking limitations such as performing a differentiation of the PSD on the spatial frequency by using the PSD function; calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; and setting a range including at least portion of the upper 25% values as the spatial-frequency interval. Lavoie, in the same field of endeavor as the claimed invention, teaches performing a differentiation of the PSD on the spatial frequency (Lavoie abstract; “local spatial orientation and frequency variation”) by using the PSD function (Lavoie [0065]; “The radial spectral power density is used to determine fractional power in at least one vessel segment”. [0153]; “In some embodiments, the segmentation technique described herein” uses “partial differential equation-based methods”. Thus, the partial differential of the PSD of the PSD on the spatial frequency can be performed); and calculating a median of the PSD (Lavoie [0081]; “In some embodiments, the sharpness metric described herein is determined based on… Radial Power Spectral Density Median”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Lavoie to include performing a differentiation of the PSD on the spatial frequency by using the PSD function; and calculating a median of the PSD; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Further, Pavani in view of Kondo and Lavoie teach using the PSD function (Lavoie [0197]-[0198]). A person of ordinary skill would have readily employed known computational analyses to quantify the median of the absolute values of slopes of the PSD, separating the absolute values into groups, selecting a group and setting a range including a portion of the group. Given Pavani in view of Lavoie’s explicit encouragement of computing a power spectral density function and comparing the image quality pattern with a predefined image quality threshold pattern (Lavoie claim 1), calculating the median of the absolute values of slopes of the PSD, separating the absolute values into groups, selecting a group and setting a range including a portion of the group would have been an obvious and predictable modification. Still lacking the limitation such as calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; and setting a range including at least portion of the upper 25% values as the spatial-frequency interval. However, Applicant has not provided criticality for calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; and setting a range including at least portion of the upper 25% values as the spatial-frequency interval. Specification para. [0089] merely states “Operation S170b of selecting the integral section may include operation S173b of calculating a median of the absolute values (which correspond to f'q in Fig. 7B) of the slopes of the PSD, operation S174b of separating data (i.e., the absolute values) into four groups by quartiles with respect to the median, and operation S175b of setting upper 25% of the data to an integral section. For example, a selected group among the four groups may include upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups. A range including at least portion of the upper 25% values may be set as the integral section”. Furthermore, intended use and other types of functional language must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable to performing the intended use, and then it meets the claim. It has been held that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations. Ex Parte Masham, 2 USPQ F.2d 1647 (1987). In a claim drawn to a process to making, the intended use must result in a manipulative difference as compared to the prior art. In Regarding claim Casey, 152 USPQ 235 (CCPA 1967); In Regarding claim Otto, 136 USPQ 458, 459 (CCPA 1963). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Lavoie to incorporate calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; and setting a range including at least portion of the upper 25% values as the spatial-frequency interval; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Claims 11, 12, 14, 15 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo, further in view of Debevec et al. (US 20100328677 A1), hereinafter Debevec. As to claim 11, Pavani teaches an inspection method comprising: providing an inspection apparatus (Pavani [0001]; “wafer image processing for use in wafer inspection”) comprising; a light receiver (Pavani fig. 1; [0022]; imaging module 4 collects scattered radiation from a wide area of surface 1); and a plurality of illuminations, wherein the plurality of illuminations are spaced apart from each other and respectively disposed at first positions corresponding to a first set of latitudes and longitudes, the first positions being arranged at latitudinal intervals along each longitude, and at longitudinal intervals along each latitude (Pavani fig. 5; [0035]; The image 5 is of the surface with a grid of repeated spacing indicating a set of latitudes and longitudes; and the images 9, 11, 13, 15 are of the features each with a grid of repeated spacing indicating a set of latitudes and longitudes. Thus, the illuminations of each image are spaced apart from each other), providing a semiconductor package including a surface (Pavani [0022]; fig. 1; “surface 1 is a semiconductor wafer”); inputting power to one or more of the plurality of illuminations to irradiate light onto the surface of the semiconductor package (Pavani [0030]; “In some embodiments, the predetermined performance metric comprises maximizing the ratio of scattered power from feature to scattered power from surface”. Thus, power is input to irradiate light onto the wafer surface); obtaining a plurality of vision images by detecting reflected light from the surface of the semiconductor package by using the light receiver (Pavani [0028]-[0029]; fig. 5; “In block 17, images of feature are acquired… In block 23, images of surface are acquired”); obtaining a bidirectional reflectance distribution function (BRDF) of the surface of the semiconductor package by using the plurality of vision images (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”); rendering the plurality of vision images by using the BRDF to obtain a rendered image (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”. Thus, a plurality of vision images is rendered using BRDF) to obtain a rendered image (Pavani fig. 3; the surface scattering model 22B) including an image information obtained by using virtual light (Pavani [0029]; “In block 22B, a scattering model is computed from the structural model of surface… Scattering model comprises information on scattered radiation in a plurality of polar and azimuthal angles. The scattered radiation is generated by scattering of an electromagnetic radiation by the surface” (emphasis added). Thus, the surface scattering model includes information obtained by using this computed model, i.e. this virtual model of scattered light), wherein the virtual light is from a plurality of virtual illuminations respectively disposed at second positions corresponding to a second set of latitudes and longitudes, and the first set of latitudes and longitudes is different from the second set of latitudes and longitudes (Pavani [0033]; claim 5; “wherein said computing a scattering model comprises: discretizing said structural model into a plurality of points located on a grid”, which is a computed scattered model grid, separate from the fig. 5 grid indicating the first set of latitudes and longitudes with “multiple points” (Pavani claim 1)), determining a measurement target of roughness of the surface (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed); selecting at least a portion of the plurality of vision images based on the latitude of each of the plurality of illuminations and the measurement target (Pavani fig. 5; [0035]; The images 9, 11, 13, 15 are of the features of the targeted pixel regions 8A, 8B, 8C, 8D each with a grid of latitudes and longitudes. Thus, there is a plurality of illuminations to acquire the plurality of images in fig. 5); obtaining a synthesis image (Pavani [0029]; structural model) of the rendered image and the at least the portion of the plurality of vision images (Pavani [0029]; “A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”); performing a two-dimensional (2D) Fourier transform (Pavani [0029]-[0030]; fig. 3; “ In some embodiments, the scattering of surface is modeled by computing a Fourier Transformation of the structural model of surface… In block 24, a filter is designed based on the scattering model of feature and scattering model of surface to achieve a predetermined filter performance metric… Consider F(θ,φ) to be the scattering model of feature, where θ is the polar angle and φ is the azimuthal angle. Similarly, consider S(θ,φ) to be the scattering model of surface. Both F and S are complex electromagnetic fields having an intensity and phase value at each θ and φ”. Thus, the Fourier transform is two-dimensional: θ and φ) on the synthesis image (Pavani [0029]; structural model) to calculate a power spectrum density (PSD) (Pavani [0029]; “A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”). However, Pavani does not explicitly disclose a semispherical housing; the light receiver is a camera, wherein the camera is a single one camera; the camera disposed at an uppermost apex of the semispherical housing, and the plurality of illuminations disposed on the semispherical housing; selecting a spatial-frequency interval of the PSD and quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval. Kondo, in the same field of endeavor as the claimed invention, teaches selecting a spatial-frequency interval of the PSD and quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval (Kondo [0037]; “First, the PSD function will be described. When a surface shape is expressed using three-dimensional coordinates (X, Y, Z), a height Z may be two-dimensionally Fourier transformed with respect to (X, Y), and a value obtained by squaring amplitude thereof may be expressed as a spatial frequency spectrum. The spatial frequency spectrum becomes a function P(fx, fy) in which (fx, fy) which are reciprocals of (X, Y) are used as variables. P(fr) obtained by expressing the function P using fr=°(fx×fx+fy×fy) indicates a power spectral density (PSD) function. The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include selecting a spatial-frequency interval of the PSD and quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitations such as a semispherical housing; the light receiver is a camera, wherein the camera is a single one camera; the camera disposed at an uppermost apex of the semispherical housing, and the plurality of illuminations disposed on the semispherical housing. Hayashi, in the same field of endeavor as the claimed invention, teaches the light receiver is a camera, wherein the camera is a single one camera (Hayashi col. 4 ln. 44-48; CCD camera 20). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Hayashi to include the light receiver is a camera, wherein the camera is a single one camera for the advantage of effectively receiving light for roughness inspection (Hayashi col. 4 ln. 43-64). Still lacking the limitations such as a semispherical housing; the camera disposed at an uppermost apex of the semispherical housing, and the plurality of illuminations disposed on the semispherical housing. Debevec, in the same field of endeavor as the claimed invention, teaches a semispherical housing (Debevec [0101]; “a rough specular hemisphere”); the camera disposed at an uppermost apex of the semispherical housing (Debevec [0101]; “The object may be observed through a hole in the apex of the hemisphere”. Thus, the light receiver, i.e. the “camera”, observing the object is disposed at the apex of the hemisphere), and the plurality of illuminations disposed on the semispherical housing (Debevec [0101]; “Light emitted by the projector may be reflected by the hemisphere onto the object, and subsequently observed by the camera. A similar geometric calibration as above may be performed to ensure a one-to-one mapping between directions and projector pixels”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Debevec to include a semispherical housing; the camera disposed at an uppermost apex of the semispherical housing, and the plurality of illuminations disposed on the semispherical housing; for the advantage of precise design applications for objects exhibiting specular reflections (Debevec [0101]). As to claim 12, Pavani teaches the inspection method of claim 11. However, Pavani in view of Kondo does not explicitly disclose wherein the uppermost apex of the semispherical housing is disposed at a latitude and a longitude of 0 degrees. Debevec, in the same field of endeavor as the claimed invention, teaches wherein, the uppermost apex of the semispherical housing is disposed at a latitude and a longitude of 0 degrees (Debevec [0101]; “The object may be observed through a hole in the apex of the hemisphere”. Thus, the latitude and longitude of the apex is 0 degrees). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Debevec to include wherein, the uppermost apex of the semispherical housing is disposed at a latitude and a longitude of 0 degrees; for the advantage of precise design applications for objects exhibiting specular reflections (Debevec [0101]). As to claim 14, Pavani teaches the inspection method of claim 11. Pavani in view of Kondo and Debevec does not explicitly disclose wherein the latitudinal interval is 15 degrees in each longitude, and the plurality of the illuminations are located between latitudes of -75 degrees to -15 degrees or 75 degrees to 15 degrees in each longitude. However, Applicant has not provided criticality for wherein the latitudinal interval is 15 degrees in each longitude, and the plurality of the illuminations are located between latitudes of -75 degrees to -15 degrees or 75 degrees to 15 degrees in each longitude. Specification para. [0036] merely states “In an embodiment, in a spherical coordinate system, the plurality of illuminations 120 may be arranged apart from one another by a latitudinal interval θd of about 15 degrees except 0 degree, from a latitude θ of about -75 degrees to a latitude θ of about 75 degrees”. Further, it has been held that finding the optimal or working ranges of a variable involves only routine skill in the art (MPEP 2144.05). In re Aller, 105 USPQ 233. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980). Peterson, 315 F.3d at 1330, 65 USPQ2d at 1382. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate wherein the latitudinal interval is 15 degrees in each longitude, and the plurality of the illuminations are located between latitudes of -75 degrees to -15 degrees or 75 degrees to 15 degrees in each longitude; for the advantage of enhanced design precision (Pavani [0023]). As to claim 15, Pavani teaches the inspection method of claim 11. Pavani in view of Kondo and Debevec does not explicitly disclose wherein the longitudinal interval is 45 degrees, and the plurality of illuminations are located between longitudes of 0 degrees to 315 degrees in each latitude. However, Applicant has not provided criticality for wherein the longitudinal interval is 45 degrees, and the plurality of illuminations are located between longitudes of 0 degrees to 315 degrees in each latitude. Specification para. [0037] merely states “In an embodiment, in a spherical coordinate system, the plurality of illuminations 120 may be arranged apart from one another by a longitudinal interval Φd of about 45 degrees, at a longitude Φ of about 0 degree to a longitude Φ of about 315 degrees”. Further, it has been held that finding the optimal or working ranges of a variable involves only routine skill in the art (MPEP 2144.05). In re Aller, 105 USPQ 233. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980). Peterson, 315 F.3d at 1330, 65 USPQ2d at 1382. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate wherein the longitudinal interval is 45 degrees, and the plurality of illuminations are located between longitudes of 0 degrees to 315 degrees in each latitude; for the advantage of enhanced design precision (Pavani [0023]). As to claim 17, Pavani teaches the inspection method of claim 11, wherein: when the measurement target is a width (Pavani [0029]; “A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated”); and wherein: when the measurement target is a height (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed” (emphasis added). Pavani in view of Kondo and Debevec does not explicitly disclose the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, each of the second latitudes has a magnitude between -15 degrees and 15 degrees, and each of the second latitudes has a magnitude between -90 degrees and -75 degrees or between 75 degrees and 90 degrees. However, Applicant has not provided criticality for the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, each of the second latitudes has a magnitude between -15 degrees and 15 degrees, and each of the second latitudes has a magnitude between -90 degrees and -75 degrees or between 75 degrees and 90 degrees. Specification para. [0048] merely states “In an embodiment, when the measurement target is a width, the at least portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at a first latitudes. Each of the first latitudes may have a value between about -15 degrees and about 15 degrees”. Specification para. [0049] merely states “In an embodiment, when the measurement target is a height, the at least portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at a second latitudes. Each of the second latitudes may have a value between about -90 degrees and -75 degrees or between about 75 degrees to about 90 degrees”. Further, it has been held that finding the optimal or working ranges of a variable involves only routine skill in the art (MPEP 2144.05). In re Aller, 105 USPQ 233. In re Boesch, 617 F.2d 272, 205 USPQ 215 (CCPA 1980). Peterson, 315 F.3d at 1330, 65 USPQ2d at 1382. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate the at least the portion of the plurality of vision images is obtained by using light from high-angle illuminations disposed at first latitudes, the at least the portion of the plurality of vision images is obtained by using light from low-angle illuminations disposed at second latitudes, each of the second latitudes has a magnitude between -15 degrees and 15 degrees, and each of the second latitudes has a magnitude between -90 degrees and -75 degrees or between 75 degrees and 90 degrees; for the advantage of enhanced design precision (Pavani [0023]). Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo and Debevec, further in view of Ohnishi et al. (US 20100259746 A1), hereinafter Ohnishi. As to claim 13, Pavani teaches the inspection method of claim 11. However, Pavani in view of Kondo and Debevec does not explicitly disclose wherein: each of the plurality of illuminations is configured so that a wavelength and an intensity of light emitted therefrom is individually adjusted by a controller, and the light emitted from each of the plurality of illuminations is a visible light. Ohnishi, in the same field of endeavor as the claimed invention, teaches wherein: each of the plurality of illuminations is configured so that a wavelength and an intensity of light emitted therefrom is individually adjusted by a controller, and the light emitted from each of the plurality of illuminations is a visible light (Ohnishi [0061]-[0062]; fig. 5A-5B; [0061]; The light emission at each position of the light emission region of the lighting device 3 is set to emit light of spectral distribution different at all positions… the light emission intensity of each component of RGB is changed with respect to different directions on the dome… the light emission intensity is set so that the light emission intensity L(θ) on the isochromatic line satisfies the relationship L(θ)=Lmin+(Lmax−Lmin)×(θ/π)” (emphasis added). Thus, the wavelength θ and intensity L(θ) are individually adjusted with respect to the components of RGB and with respect to different directions on the dome. Further, RGB is in the visible spectrum and thus, light from each of the plurality of illuminations is a visible light). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate the teachings of Ohnishi to include wherein: each of the plurality of illuminations is configured so that a wavelength and an intensity of light emitted therefrom is individually adjusted by a controller, and the light emitted from each of the plurality of illuminations is a visible light; for the advantage of multispectral usage to provide more detailed information for accurate measurement of surface (Ohnishi [0061]). PNG media_image5.png 661 496 media_image5.png Greyscale Ohnishi Fig. 5A-5B Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo and Debevec, further in view of Lavoie. As to claim 16, Pavani teaches the inspection method of claim 11, wherein the selecting of the integral section of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added)) comprises: changing the PSD to a PSD function, wherein the PSD is a function of a spatial frequency (Pavani [0029]; “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency); and setting a range including at least a portion of the plurality of PSD points as the integral section (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter”. [0031]; “A(θ,φ) comprises information on the range of scattering angles collected by the imaging module” (emphasis added)). However, Pavani does not explicitly disclose the integral section is the spatial-frequency interval; performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function, wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Kondo, in the same field of endeavor as the claimed invention, teaches the integral section is the spatial-frequency interval (Kondo [0037]; The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral section is the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking limitations such as performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function, wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Lavoie, in the same field of endeavor as the claimed invention, teaches performing a differentiation of the PSD on the spatial frequency (Lavoie abstract; “local spatial orientation and frequency variation”) by using the PSD function (Lavoie [0065]; “The radial spectral power density is used to determine fractional power in at least one vessel segment”. [0153]; “In some embodiments, the segmentation technique described herein” uses “partial differential equation-based methods”. Thus, the partial differential of the PSD of the PSD on the spatial frequency can be performed); setting a threshold value (Lavoie claim 1; “(b) comparing the image quality pattern obtained in (a) with a predefined image quality threshold pattern, wherein the quality threshold pattern comprises at least one threshold”); selecting a plurality of PSD points in a graph of the PSD function (Lavoie [0198]; “The term “angular spectral power density”, as used herein, refers to the angularly (over a certain range of orientation, for 0 to 180 degrees) average value of the spectral power density. Therefore, the angular spectral power can represent the density distribution of the power spectral density as a function of angle or orientation, over the range 0 to 180 degrees, in the image” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate the teachings of Lavoie to include performing a differentiation of the PSD on the spatial frequency by using the PSD function; setting a threshold value; selecting a plurality of PSD points in a graph of the PSD function; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Further, Pavani in view of Kondo and Debevec and Lavoie teach using the PSD function (Lavoie [0197]-[0198]). A person of ordinary skill would have readily employed known computational analyses to quantify the absolute values of slopes at each of the plurality of PSD points, and compare them to a threshold value. Given Pavani in view of Lavoie’s explicit encouragement of computing a power spectral density function and comparing the image quality pattern with a predefined image quality threshold pattern (Lavoie claim 1), measuring the power spectral density graph and correlating the absolute value of the slopes to the threshold would have been an obvious and predictable modification. Still lacking the limitation such as wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. However, Applicant has not provided criticality for wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value. Specification para. [0084] merely states “FIG. 7B is a graph showing a correlation of a slope absolute value of a power energy spectrum density with respect to a space frequency, according to an embodiment”. Specification para. [0086] merely states “In an embodiment, when a threshold value is set to 10, PSD points at which the absolute value f'q of the slope of the PSD is greater than or equal to the threshold value may correspond to PSD points denoted by circles in the graph of FIG. 7B”. Furthermore, intended use and other types of functional language must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable to performing the intended use, and then it meets the claim. It has been held that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations. Ex Parte Masham, 2 USPQ F.2d 1647 (1987). In a claim drawn to a process to making, the intended use must result in a manipulative difference as compared to the prior art. In Regarding claim Casey, 152 USPQ 235 (CCPA 1967); In Regarding claim Otto, 136 USPQ 458, 459 (CCPA 1963). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec and Lavoie to incorporate wherein absolute values of slopes at each of the plurality of PSD points is greater than or equal to the threshold value; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo and Debevec, further in view of Institute of Aeronautical Engineering (Institute of Aeronautical Engineering, (2022, February 8). Relationship between Power Spectral Density and Autocorrelation Function by Ms. B Mary Swarnalatha [Video]. YouTube. https://www.youtube.com/watch?v=XUbsweljooE&t=28s). As to claim 18, Pavani teaches the inspection method of claim 17, wherein the performing of the integral on the PSD comprises: calculating an integral value of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added). “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency); setting an index value based on the measurement target (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed. Further, an autocorrelation of surface profile is computed. A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated. A total integrated scatter is calculated from the ensemble roughness metric, correlation length, angle of incidence of electromagnetic beam, and wavelength of electromagnetic radiation” (emphasis added). Thus, the total integrated scatter is set based on the ensemble roughness metric); and obtaining a correlation function corresponding to a relationship between the index value and the PSD (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed. Further, an autocorrelation of surface profile is computed. A correlation length, a parameter quantifying the width of the autocorrelation plot, is estimated. A total integrated scatter is calculated from the ensemble roughness metric, correlation length, angle of incidence of electromagnetic beam, and wavelength of electromagnetic radiation. A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile” (emphasis added). Thus, the autocorrelation function is obtained corresponding to a relationship between the ensemble roughness metric and the PSD). However, Pavani does not explicitly disclose the integral value of the PSD of a spatial frequency in the spatial-frequency interval; wherein the correlation function is a first-order function, a second-order function, a third-order function, or an exponential function. Kondo, in the same field of endeavor as the claimed invention, teaches the integral value of the PSD of a spatial frequency in the spatial-frequency interval (Kondo [0047]; “Next, the procedure of calculating the surface roughness from the PSD function will be described... The RMS roughness becomes a value obtained by integrating a product of a PSD function 401 and a spatial, frequency f in a certain spatial frequency band (band f1 to f2 in FIG. 4). When an integration interval f1 to f2 is arbitrarily selected and the RMS roughness in the interval is set as RMS(f1, f2), RMS(f1, f2)=√(2π∫f2 f1PSD(f)×fdf)”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral value of the PSD of a spatial frequency in the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitation such as wherein the correlation function is a first-order function, a second-order function, a third-order function, or an exponential function. Institute of Aeronautical Engineering, in the same field of endeavor as the claimed invention, teaches wherein the correlation function is a first-order function, a second-order function, a third-order function, or an exponential function (Institute of Aeronautical Engineering timestamps -37.02 and -22.33; The autocorrelation function Rxx(τ), i.e. “Rxx(t1, t-2)”, is an inverse FT of power spectral density, and generally is a second-order function, measuring the intensity correlation of light at two different times t1 and t-2). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Debevec to incorporate the teachings of Institute of Aeronautical Engineering to include wherein the correlation function is a first-order function, a second-order function, a third-order function, or an exponential function; for the advantage of improved modeling. Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo, further in view of Nagano et al. (US 20190244336 A1), hereinafter Nagano. As to claim 19, Pavani teaches a method comprising: preparing a wafer (Pavani [0022]; “FIG. 1 shows an imaging module 4 collecting scattered radiation from a wide area of a surface 1 and focusing the radiation on an image sensor 5, in accordance with the invention. A feature 2 present on surface 1 scatters electromagnetic radiation incident on it. In some embodiments, surface 1 is a semiconductor wafer” (emphasis added)); performing a semiconductor manufacturing process on the wafer to obtain a semiconductor package (Pavani [0002]; “Semiconductor wafers are used in the fabrication of integrated circuits (ICs) that drive modern electronic devices”); and inspecting the semiconductor package (Pavani [0001]; “wafer image processing for use in wafer inspection”), wherein the inspecting of the semiconductor package comprises: obtaining a plurality of vision images of a surface of the semiconductor package by using light from a plurality of illuminations with respect to an illumination designation region (Pavani [0028]-[0029]; fig. 5; “In block 17, images of feature are acquired… In block 23, images of surface are acquired”. Thus, there is a plurality of illuminations to acquire the plurality of images in fig. 5); obtaining a bidirectional reflectance distribution function (BRDF) of the surface of the semiconductor package by using the plurality of vision images (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”); obtaining a rendered image including image information obtained by using virtual light by using the BRDF with respect to an illumination non-designation region (Pavani [0029]; fig. 3; “In block 23, images of surface are acquired… In block 20, a structural model for surface is generated by extracting predetermined properties from acquired images of surface... In block 22B, a scattering model is computed from the structural model of surface… In some embodiments, a bidirectional reflection distribution function is used to calculate the scattering model of surface”. Thus, a plurality of vision images is rendered using BRDF); determining a measurement target of roughness of the surface of the semiconductor package (Pavani [0029]; “In some embodiments, an ensemble roughness metric for surface height deviation (relative to an average surface height value), such as a root mean square deviation, is computed” (emphasis added)); selecting at least a portion of the plurality of vision images based on a position of each of the plurality of illuminations and the measurement target (Pavani fig. 5; [0035]; The images 9, 11, 13, 15 are of the features of the targeted pixel regions 8A, 8B, 8C, 8D each with a grid of latitudes and longitudes. Thus, there is a plurality of illuminations to acquire the plurality of images in fig. 5); performing a two-dimensional (2D) Fourier transform (Pavani [0029]-[0030]; fig. 3; “ In some embodiments, the scattering of surface is modeled by computing a Fourier Transformation of the structural model of surface… In block 24, a filter is designed based on the scattering model of feature and scattering model of surface to achieve a predetermined filter performance metric… Consider F(θ,φ) to be the scattering model of feature, where θ is the polar angle and φ is the azimuthal angle. Similarly, consider S(θ,φ) to be the scattering model of surface. Both F and S are complex electromagnetic fields having an intensity and phase value at each θ and φ”. Thus, the Fourier transform is two-dimensional: θ and φ) on a first synthesis image of the rendered image (Pavani [0029]; structural model) and the at least portion of the plurality of vision images to obtain a power spectrum density (PSD) of the surface (Pavani [0029]; “A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”); selecting a spatial-frequency interval of the PSD (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter” (emphasis added)). However, Pavani does not explicitly disclose the method is a semiconductor manufacturing method; and quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval. Kondo, in the same field of endeavor as the claimed invention, teaches quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval (Kondo [0037]; “First, the PSD function will be described. When a surface shape is expressed using three-dimensional coordinates (X, Y, Z), a height Z may be two-dimensionally Fourier transformed with respect to (X, Y), and a value obtained by squaring amplitude thereof may be expressed as a spatial frequency spectrum. The spatial frequency spectrum becomes a function P(fx, fy) in which (fx, fy) which are reciprocals of (X, Y) are used as variables. P(fr) obtained by expressing the function P using fr=°(fx×fx+fy×fy) indicates a power spectral density (PSD) function. The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum” (emphasis added)). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include quantifying the roughness of the surface by performing an integral on the PSD over the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitation such as the method is a semiconductor manufacturing method. Nagano, in the same field of endeavor as the claimed invention, teaches the method is a semiconductor manufacturing method (Nagano claim 16; “A semiconductor device manufacturing method using a defect inspection apparatus”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo to incorporate the teachings of Nagano to include the method is a semiconductor manufacturing method, for the advantage of real-time in-line manufacturing (Nagano [0026]). Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Pavani in view of Kondo and Nagano, further in view of Lavoie. As to claim 20, Pavani teaches the semiconductor manufacturing method of claim 19, wherein the selecting of the integral section of the PSD comprises: changing the PSD to a PSD function, wherein the PSD is a function of a spatial frequency (Pavani [0029]; “In block 22B… A power spectral density function is computed as the Fourier transform of the autocorrelation of surface profile”. [0031]; fig. 3; the feature spread function in block 26 is computed by transforming it “from spatial frequency domain to image domain”. Thus, the blocks prior to blocks 25 and 26 are in the spatial frequency domain. Therefore, the PSD at block 22B is a function of spatial frequency); and setting a range including at least a portion of the upper 25% values as the integral section (Pavani [0029]; “In some embodiments, the scattering of surface modeled from the power spectral density function is normalized so that the integral of power spectral density function is equal to total integrated scatter”. [0031]; “A(θ,φ) comprises information on the range of scattering angles collected by the imaging module” (emphasis added)). However, Pavani does not explicitly disclose the integral section is the spatial-frequency interval; performing a differentiation of the PSD on the spatial frequency by using the PSD function; calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups. Kondo, in the same field of endeavor as the claimed invention, teaches the integral section is the spatial-frequency interval (Kondo [0037]; The PSD function has the size of a surface roughness and cycle information. That is, the PSD function may be expressed as an example of a function that expresses the spatial frequency spectrum”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani to incorporate the teachings of Kondo to include the integral section is the spatial-frequency interval; for the advantage of enhanced techniques of measuring micro roughness in a short amount of time (Kondo [0007]-[0008]). Still lacking the limitations such as performing a differentiation of the PSD on the spatial frequency by using the PSD function; calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups. Lavoie, in the same field of endeavor as the claimed invention, teaches performing a differentiation of the PSD on the spatial frequency (Lavoie abstract; “local spatial orientation and frequency variation”) by using the PSD function (Lavoie [0065]; “The radial spectral power density is used to determine fractional power in at least one vessel segment”. [0153]; “In some embodiments, the segmentation technique described herein” uses “partial differential equation-based methods”. Thus, the partial differential of the PSD of the PSD on the spatial frequency can be performed); and calculating a median of the PSD (Lavoie [0081]; “In some embodiments, the sharpness metric described herein is determined based on… Radial Power Spectral Density Median”). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo and Nagano to incorporate the teachings of Lavoie to include performing a differentiation of the PSD on the spatial frequency by using the PSD function; and calculating a median of the PSD; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Further, Pavani in view of Kondo, Nagano and Lavoie teach using the PSD function (Lavoie [0197]-[0198]). A person of ordinary skill would have readily employed known computational analyses to quantify the median of the absolute values of slopes of the PSD, separating the absolute values into groups and selecting a group. Given Pavani in view of Lavoie’s explicit encouragement of computing a power spectral density function and comparing the image quality pattern with a predefined image quality threshold pattern (Lavoie claim 1), calculating the median of the absolute values of slopes of the PSD, separating the absolute values into groups and selecting a group would have been an obvious and predictable modification. Still lacking the limitation such as calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups. However, Applicant has not provided criticality for calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups. Specification para. [0089] merely states “Operation S170b of selecting the integral section may include operation S173b of calculating a median of the absolute values (which correspond to f'q in Fig. 7B) of the slopes of the PSD, operation S174b of separating data (i.e., the absolute values) into four groups by quartiles with respect to the median, and operation S175b of setting upper 25% of the data to an integral section. For example, a selected group among the four groups may include upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups”. Furthermore, intended use and other types of functional language must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. If the prior art structure is capable to performing the intended use, and then it meets the claim. It has been held that a recitation with respect to the manner in which a claimed apparatus is intended to be employed does not differentiate the claimed apparatus from a prior art apparatus satisfying the claimed structural limitations. Ex Parte Masham, 2 USPQ F.2d 1647 (1987). In a claim drawn to a process to making, the intended use must result in a manipulative difference as compared to the prior art. In Regarding claim Casey, 152 USPQ 235 (CCPA 1967); In Regarding claim Otto, 136 USPQ 458, 459 (CCPA 1963). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify Pavani in view of Kondo, Nagano and Lavoie to incorporate calculating a median of absolute values of slopes of the PSD; separating the absolute values into four groups by quartiles with respect to the median; selecting a selected group among the four groups, wherein the selected group includes upper 25% values among the absolute values, and each of the upper 25% values is greater than values of unselected groups among the four groups; for the advantage of classification and improvement of the quality of the computed image (Lavoie [0012]-[0013]). Conclusion Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEMAYA NGUYEN whose telephone number is (571)272-9078. The examiner can normally be reached Mon - Fri 8:30 am - 5:00pm ET. 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