DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
2. Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
3. The information disclosure statement (IDS) submitted on 06/24/2024. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
CLAIM INTERPRETATION
4. The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
5. The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP §2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word "means," but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
obtaining unit in claim 1
control unit in claims 1, 3-10, 12 and 13
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
6. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
7. 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, 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.
8. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
9. Claim(s) 1-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chatterjee et al. (US 2020/0184633 A1) in view of Itagaki et al. (US 2007/0153340 A1).
10. With reference to claim 1, Chatterjee teaches An image processing apparatus (“Referring to FIG. 1, enclosure 110 includes a plurality of light sources 120, lens 130, camera 140, and image processing system 150. Located within enclosure 110 are gauge 160 and wide gamut color chart 170. In this embodiment, image processing system 150 is coupled to data processing and printing system 190 via network 165. The data processing and printing system produces custom color calibration chart 180.” [0030] “Coupled to enclosure 810 are lens 830, camera 840, and image processing circuit 850.” [0048]) Chatterjee also teaches an obtaining unit configured to obtain spectral reflectances of a plurality of color patches; (“Measurement of color is most commonly achieved by using a contact spectrophotometer which uses an integrating sphere for accurate radiometric measurement of the spectral reflectance and its subsequent conversion to photometric units.” [0003] “Embodiments of this disclosure can include a wide gamut calibration chart (reference target) designed to contain colors within all reproducible colors. The use of the wide gamut calibration chart can be serialized so each color patch is measured and software can read up a data file for the spectral values for each color patch.” [0033] “Spectral values allow computation for different illuminants. This allows the software to calibrate between known spectral reflectance values and RGB for each patch and create a model with the multiple color patches.” [0037]) Chatterjee further teaches a control unit configured to generate design data of a color chart including a plurality of color patches selected so as to reduce an evaluation value E of the color chart (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “Embodiments of this disclosure can include creating a customer color calibration chart with the ability to manually pick colors that are to be included on the calibration targe” [0057] “The color target produced is then measured with a photo-spectrometer. Each patch is measured and the errors of the measured colors with respect to the intended colors are computed. A standard photo spectrometer like the Xrite i1 or Datacolor Spyder can be used to measure the target. The spectral data is used to compute LAB values with specific illuminants and observers. Errors between the intended colors and the measured colors are then computed. Errors are computed for each component of color, L, a, and b. A standard measure of the total error like Delta_E (ΔE*.sub.ab) which is defined as the root mean square of the differences of each component is used as the single error value that will be minimized. … Using the regression model a new color target is defined that when printed will reduce the errors between the new intended colors and the measured colors. Only one iteration of this process is typically necessary unless the patch error is large (typically greater than 2). If the errors are larger than a specific threshold, typically 2, the intended, specified colors are replaced with the printed and measured colors and the process is repeated until the errors are reduced.” [0069-0071])
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Chatterjee does not explicitly teach evaluation value E calculated based on Equation (I) from the spectral reflectances of the plurality of color patches.
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This is what Itagaki teaches (“When the user sets the homogeneity in page image evaluation chart (output sample 42) output from the printer 41 on the spectrometer 43, the color evaluation program 22 controls the spectrometer 43 to measure the spectral reflectance of the homogeneity in page image evaluation chart (S106). The program 22 receives the measured data (S107), and calculates the homogeneity in page image (S108).” [0072] “When the user sets the evaluation chart (output sample 42) output from the printer 41 on the spectrometer 43, the color evaluation program 22 controls the spectrometer 43 to measure the spectral reflectance of the evaluation chart (S119). The program 22 receives the measured data (colorimetric data associated with the spectral reflectance) (S120), and calculates color matching precision (S121). This calculation computes the color differences (color matching precision) of respective patches by comparing the spectral reflectance characteristics 32 of the color target 31 loaded in step S114 with the measurement result.” [0079] “Note that the same evaluation chart and homogeneity in page image evaluation chart as those in the first embodiment are used. Therefore, the following explanation will be given under the assumption that a uniform chart of C, M, and Y=20% is used as the homogeneity in page image evaluation chart, and the ISO12642 928 patches are used as the evaluation chart. However, the first embodiment evaluates the homogeneity in page image using the segments of 13 rows.times.16 columns, as shown in FIG. 8. However, the second embodiment adopts the same segments as in the ISO12642 928 patches, and uses matched measurement positions. That is, the segments of 26 rows.times.38 columns (total of 988 segments) shown in FIG. 6 are measured. Note that 60 patches which are not included in the ISO12642 928 patches are measured, and the maximum color difference Max. .DELTA.E, minimum color difference Min. .DELTA.E, and average color difference Ave. .DELTA.E, which are described in the first embodiment, are calculated together with the 928 patches.” [0095] “The second embodiment uses equation (2) to calculate a color difference .DELTA.Eu of the homogeneity in page image. Also, this embodiment uses equation (3) to calculate the color difference .DELTA.E of the color matching precision.” [0098] “Equation (4) describes a calculation equation of the color difference .DELTA.Em of color matching attained by subtracting the color difference Eup of the homogeneity in page image from the color difference Ecp of the patch. … equation (5) represents the ratio of the color difference Eu of the homogeneity in page image included in color matching precision Ec. The color matching precision Ec can be expressed by a calculation equation that indicates the degree of influence of the homogeneity in page image or the including ratio of the influence of the homogeneity in page image. In other words, the calculations and display method that allow for separation of the factors of color matching precision can be used.” [0109-0110]) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Itagaki into Chatterjee, in order to determine the color matching precision.
11. With reference to claim 2, Chatterjee teaches the plurality of color patches for the color chart are selected (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “Embodiments of this disclosure can include creating a customer color calibration chart with the ability to manually pick colors that are to be included on the calibration targe” [0057])
Chatterjee does not explicitly teach such that the evaluation value E is less than or equal to 0.7. This is what Itagaki teaches (“in considering the measurement errors of the measuring instrument, the stability of an image forming apparatus, the number of grids and interpolation calculations of an ICC profile, and the like, if the color difference .DELTA.Em of color matching<1, there is no need to re-prepare the ICC profile. In order to further improve the color matching precision, the image forming apparatus should be adjusted to reduce heterogeneity in page image rather than re-preparation of the ICC profile.” [0107] “The color evaluation program 22 makes a decision to pass or fail by checking whether or not the maximum density and tone reproducibility fall within a permissible range (S209). Note that the fourth embodiment sets a permissible range so that the absolute values of density variations with respect to a target density value fall within the range (target density.times.0.07.+-.0.01). 7% approximately represents a change of .DELTA.E=2, and 0.01 makes an allowance for errors of the measuring instrument. Alternatively, the maximum density and tone reproducibility may be checked using a color difference in place of the density value.” [0140]) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Itagaki into Chatterjee, in order to determine the color matching precision.
12. With reference to claim 3, Chatterjee teaches the control unit generates first tentative design data, which includes the selected plurality of color patches, and, in a case where an evaluation value E of second tentative design data to which a color patch not included in the first tentative design data has been added is smaller than an evaluation value E of the first tentative design data, sets the second tentative design data as new tentative design data. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “Embodiments of this disclosure can include creating a customer color calibration chart with the ability to manually pick colors that are to be included on the calibration targe” [0057] “The color target produced is then measured with a photo-spectrometer. Each patch is measured and the errors of the measured colors with respect to the intended colors are computed. A standard photo spectrometer like the Xrite i1 or Datacolor Spyder can be used to measure the target. The spectral data is used to compute LAB values with specific illuminants and observers. Errors between the intended colors and the measured colors are then computed. Errors are computed for each component of color, L, a, and b. A standard measure of the total error like Delta_E (ΔE*.sub.ab) which is defined as the root mean square of the differences of each component is used as the single error value that will be minimized. … if the errors are larger than a specific threshold, typically 2, the intended colors are replaced with the measured colors. If the errors are smaller than the threshold the patches are combined with the colors measured on all the other patches to create a regression model between the intended and printed colors. Using the regression model a new color target is defined that when printed will reduce the errors between the new intended colors and the measured colors. Only one iteration of this process is typically necessary unless the patch error is large (typically greater than 2). If the errors are larger than a specific threshold, typically 2, the intended, specified colors are replaced with the printed and measured colors and the process is repeated until the errors are reduced.” [0069-0071])
13. With reference to claim 4, Chatterjee teaches the control unit adds a color patch and updates the tentative design data until the number of color patches of the tentative design data reaches a predetermined number. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “The maximum number of colors patches is picked using a reasonable size for each patch and the maximum dimensions of the target. A fraction of this number, typically 30%, of the patches is picked by randomly sampling the outer surface of the gamut of all colors. This is important and these can be termed “boundary colors.” In a preferred embodiment, colors are picked from all parts of the gamut.” [0066] “The color target produced is then measured with a photo-spectrometer. Each patch is measured and the errors of the measured colors with respect to the intended colors are computed. A standard photo spectrometer like the Xrite i1 or Datacolor Spyder can be used to measure the target. The spectral data is used to compute LAB values with specific illuminants and observers. Errors between the intended colors and the measured colors are then computed. Errors are computed for each component of color, L, a, and b. A standard measure of the total error like Delta_E (ΔE*.sub.ab) which is defined as the root mean square of the differences of each component is used as the single error value that will be minimized. … if the errors are larger than a specific threshold, typically 2, the intended colors are replaced with the measured colors. If the errors are smaller than the threshold the patches are combined with the colors measured on all the other patches to create a regression model between the intended and printed colors. Using the regression model a new color target is defined that when printed will reduce the errors between the new intended colors and the measured colors. Only one iteration of this process is typically necessary unless the patch error is large (typically greater than 2). If the errors are larger than a specific threshold, typically 2, the intended, specified colors are replaced with the printed and measured colors and the process is repeated until the errors are reduced.” [0069-0071])
14. With reference to claim 5, Chatterjee teaches the control unit generates a plurality of pieces of tentative design data whose number of color patches is the predetermined number and sets tentative design data whose evaluation value E is the smallest as the design data. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “The maximum number of colors patches is picked using a reasonable size for each patch and the maximum dimensions of the target. A fraction of this number, typically 30%, of the patches is picked by randomly sampling the outer surface of the gamut of all colors. This is important and these can be termed “boundary colors.” In a preferred embodiment, colors are picked from all parts of the gamut.” [0066] “The color target produced is then measured with a photo-spectrometer. Each patch is measured and the errors of the measured colors with respect to the intended colors are computed. A standard photo spectrometer like the Xrite i1 or Datacolor Spyder can be used to measure the target. The spectral data is used to compute LAB values with specific illuminants and observers. Errors between the intended colors and the measured colors are then computed. Errors are computed for each component of color, L, a, and b. A standard measure of the total error like Delta_E (ΔE*.sub.ab) which is defined as the root mean square of the differences of each component is used as the single error value that will be minimized. … if the errors are larger than a specific threshold, typically 2, the intended colors are replaced with the measured colors. If the errors are smaller than the threshold the patches are combined with the colors measured on all the other patches to create a regression model between the intended and printed colors. Using the regression model a new color target is defined that when printed will reduce the errors between the new intended colors and the measured colors. Only one iteration of this process is typically necessary unless the patch error is large (typically greater than 2). If the errors are larger than a specific threshold, typically 2, the intended, specified colors are replaced with the printed and measured colors and the process is repeated until the errors are reduced.” [0069-0071])
15. With reference to claim 6, Chatterjee teaches the control unit generates the design data, which includes a plurality of color patches each having a highest reflectance peak in spectral wavelengths greater than or equal to 600 nm. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “the workpiece is illuminated with all wavelengths excluding the excitation wavelengths and the reflectance for all these non-fluorescence wavelengths is measured. Second, the workpiece is illuminated with each excitation wavelength and the reflectance is measured at that specific wavelength together with the fluorescence. This data can then be combined, optionally with other images, to estimate the reflectance in the entire color space.” [0040] “The inner wall material can advantageously be optically opaque to eliminate any light from entering the enclosure. A preferred material for the inner wall material is plastic (for low cost) or ceramic for high temperature resistance. An outer wall provides mechanical protection and protection from dust, fluids, and other environmental factors found in a laboratory or factory setting. A preferred material for the outer wall is metal such as stainless steel or anodized aluminum.” [0049-0050] “This ensures that the production of new application calibration charts with different materials or production process does not result in large measurement errors.” [0088] “At least one patch is a shade of gray that is close to the highest reflectance of the workpiece but does not exceed it.” [0092] “manufactured or natural materials like Formica countertops, carpets, laminates, borehole cores from oil wells etc. … Embodiments can be used to characterize borehole core material such as color analysis to determine geological features. Embodiments can be used for inspection of a collection of workpieces e.g. wood cores, vegetables or fruits, processed snack foods, etc.” [0099])
16. With reference to claim 7, Chatterjee teaches the control unit generates the design data, which includes a plurality of color patch materials each having a highest reflectance peak in spectral wavelengths from 500 nm to 540 nm. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “the workpiece is illuminated with all wavelengths excluding the excitation wavelengths and the reflectance for all these non-fluorescence wavelengths is measured. Second, the workpiece is illuminated with each excitation wavelength and the reflectance is measured at that specific wavelength together with the fluorescence. This data can then be combined, optionally with other images, to estimate the reflectance in the entire color space.” [0040] “The inner wall material can advantageously be optically opaque to eliminate any light from entering the enclosure. A preferred material for the inner wall material is plastic (for low cost) or ceramic for high temperature resistance. An outer wall provides mechanical protection and protection from dust, fluids, and other environmental factors found in a laboratory or factory setting. A preferred material for the outer wall is metal such as stainless steel or anodized aluminum.” [0049-0050] “This ensures that the production of new application calibration charts with different materials or production process does not result in large measurement errors.” [0088] “At least one patch is a shade of gray that is close to the highest reflectance of the workpiece but does not exceed it.” [0092] “manufactured or natural materials like Formica countertops, carpets, laminates, borehole cores from oil wells etc. … Embodiments can be used to characterize borehole core material such as color analysis to determine geological features. Embodiments can be used for inspection of a collection of workpieces e.g. wood cores, vegetables or fruits, processed snack foods, etc.” [0099])
17. With reference to claim 8, Chatterjee teaches the control unit generates the design data, which includes a plurality of color patch materials each having a highest reflectance peak in spectral wavelengths from 440 nm to 470 nm. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “the workpiece is illuminated with all wavelengths excluding the excitation wavelengths and the reflectance for all these non-fluorescence wavelengths is measured. Second, the workpiece is illuminated with each excitation wavelength and the reflectance is measured at that specific wavelength together with the fluorescence. This data can then be combined, optionally with other images, to estimate the reflectance in the entire color space.” [0040] “The inner wall material can advantageously be optically opaque to eliminate any light from entering the enclosure. A preferred material for the inner wall material is plastic (for low cost) or ceramic for high temperature resistance. An outer wall provides mechanical protection and protection from dust, fluids, and other environmental factors found in a laboratory or factory setting. A preferred material for the outer wall is metal such as stainless steel or anodized aluminum.” [0049-0050] “This ensures that the production of new application calibration charts with different materials or production process does not result in large measurement errors.” [0088] “At least one patch is a shade of gray that is close to the highest reflectance of the workpiece but does not exceed it.” [0092] “manufactured or natural materials like Formica countertops, carpets, laminates, borehole cores from oil wells etc. … Embodiments can be used to characterize borehole core material such as color analysis to determine geological features. Embodiments can be used for inspection of a collection of workpieces e.g. wood cores, vegetables or fruits, processed snack foods, etc.” [0099])
18. With reference to claim 9, Chatterjee teaches the control unit generates the design data based on the number of a plurality of color patches to be arranged in the color chart inputted by a user. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “The monitor(s) can be for one or more users to interact with a system computer. The monitor(s) can be for one or more users to initiate color measurements on the workpiece. The monitor(s) can be for one or more users to view color measurements on the workpiece. The monitor(s) can be for one or more users to view the result of a color based inspection on the workpiece. The monitor(s) can be for one or more users to review statistical results of multiple workpieces that have been inspected. The monitor(s) can be for one or more users to perform calibration. The monitor(s) can be for one or more users to initiate other actions e.g. save images, define new workpieces, etc.” [0046])
19. With reference to claim 10, Chatterjee teaches the control unit generates the design data based on a size of the color chart inputted by a user. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “Spectral values allow computation for different illuminants. This allows the software to calibrate between known spectral reflectance values and RGB for each patch and create a model with the multiple color patches. More patches can be used. More colors lead to more accuracy for a given size of the color gamut.” [0037] “The monitor(s) can be for one or more users to interact with a system computer. The monitor(s) can be for one or more users to initiate color measurements on the workpiece. The monitor(s) can be for one or more users to view color measurements on the workpiece. The monitor(s) can be for one or more users to view the result of a color based inspection on the workpiece. The monitor(s) can be for one or more users to review statistical results of multiple workpieces that have been inspected. The monitor(s) can be for one or more users to perform calibration. The monitor(s) can be for one or more users to initiate other actions e.g. save images, define new workpieces, etc.” [0046] “The maximum number of colors patches is picked using a reasonable size for each patch and the maximum dimensions of the target.” [0066])
20. With reference to claim 11, Chatterjee teaches in a case where the size of the color chart is not compatible with the number of the selected plurality of color patches, the control unit outputs an error. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “Spectral values allow computation for different illuminants. This allows the software to calibrate between known spectral reflectance values and RGB for each patch and create a model with the multiple color patches. More patches can be used. More colors lead to more accuracy for a given size of the color gamut.” [0037] “The monitor(s) can be for one or more users to interact with a system computer. The monitor(s) can be for one or more users to initiate color measurements on the workpiece. The monitor(s) can be for one or more users to view color measurements on the workpiece. The monitor(s) can be for one or more users to view the result of a color based inspection on the workpiece. The monitor(s) can be for one or more users to review statistical results of multiple workpieces that have been inspected. The monitor(s) can be for one or more users to perform calibration. The monitor(s) can be for one or more users to initiate other actions e.g. save images, define new workpieces, etc.” [0046] “The maximum number of colors patches is picked using a reasonable size for each patch and the maximum dimensions of the target.” [0066] “The color target produced is then measured with a photo-spectrometer. Each patch is measured and the errors of the measured colors with respect to the intended colors are computed. A standard photo spectrometer like the Xrite i1 or Datacolor Spyder can be used to measure the target. The spectral data is used to compute LAB values with specific illuminants and observers. Errors between the intended colors and the measured colors are then computed. Errors are computed for each component of color, L, a, and b. A standard measure of the total error like Delta_E (ΔE*.sub.ab) which is defined as the root mean square of the differences of each component is used as the single error value that will be minimized. … if the errors are larger than a specific threshold, typically 2, the intended colors are replaced with the measured colors. If the errors are smaller than the threshold the patches are combined with the colors measured on all the other patches to create a regression model between the intended and printed colors. Using the regression model a new color target is defined that when printed will reduce the errors between the new intended colors and the measured colors. Only one iteration of this process is typically necessary unless the patch error is large (typically greater than 2). If the errors are larger than a specific threshold, typically 2, the intended, specified colors are replaced with the printed and measured colors and the process is repeated until the errors are reduced.” [0069-0071])
21. With reference to claim 12, Chatterjee teaches the control unit displays the color chart including the selected plurality of color patches. (“Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0034] “The monitor(s) can be for one or more users to interact with a system computer. The monitor(s) can be for one or more users to initiate color measurements on the workpiece. The monitor(s) can be for one or more users to view color measurements on the workpiece. The monitor(s) can be for one or more users to view the result of a color based inspection on the workpiece. The monitor(s) can be for one or more users to review statistical results of multiple workpieces that have been inspected. The monitor(s) can be for one or more users to perform calibration. The monitor(s) can be for one or more users to initiate other actions e.g. save images, define new workpieces, etc.” [0046] “Embodiments of this disclosure can include creating a customer color calibration chart with the ability to manually pick colors that are to be included on the calibration targe” [0057])
22. With reference to claim 13, Chatterjee teaches the control unit displays a completion plan diagram of the color chart including the selected plurality of color patches. (“Embodiments of this disclosure can include a wide gamut calibration chart (reference target) designed to contain colors within all reproducible colors. The use of the wide gamut calibration chart can be serialized so each color patch is measured and software can read up a data file for the spectral values for each color patch. … Embodiments of this disclosure can include a custom color calibration chart (calibration target) designed to contain colors within the gamut of interest. This can be termed to be a workpiece specific color chart. Referring to FIG. 3, custom color calibration chart 300 can include grid of color patches 310. Of course, the color patches can be spatially arranged in other ways such as radially or even three dimensionally. The custom color calibration chart can include fiducials 320 for orientation. The custom color calibration chart can include bar code 330 for serialization. The custom color calibration chart can include one or more focusing bars 340. The use of the custom color calibration chart can be serialized and the imaging sequential so each color patch is measured and software can read up the spectral values for each color patch.” [0033-0034] “The monitor(s) can be for one or more users to interact with a system computer. The monitor(s) can be for one or more users to initiate color measurements on the workpiece. The monitor(s) can be for one or more users to view color measurements on the workpiece. The monitor(s) can be for one or more users to view the result of a color based inspection on the workpiece. The monitor(s) can be for one or more users to review statistical results of multiple workpieces that have been inspected. The monitor(s) can be for one or more users to perform calibration. The monitor(s) can be for one or more users to initiate other actions e.g. save images, define new workpieces, etc.” [0046] “Embodiments of this disclosure can include creating a customer color calibration chart with the ability to manually pick colors that are to be included on the calibration targe” [0057] “a process can begin with a quantized sampling of a CIE Lab gamut 510. Then, a layout of color in chart format 520 is created. Then, the colors are printed 530. Then, the printed colors are measured 540. Then, for each of the measured colors, a determination of whether Delta_E is within a tolerance 550 is performed. If the measured colors are within tolerance, then the specification file for wide gamut color target 570 is complete. If the measured colors are not within tolerance, then the colors are refined 560 and the process repeats starting at layout 520.” [0065])
23. Claim 14 is similar in scope to claim 1, and thus is rejected under similar rationale.
24. Claim 15 is similar in scope to claim 1, and thus is rejected under similar rationale. Chatterjee does not explicitly teach A non-transitory computer-readable storage medium storing a computer program to be read and executed by a computer. This is what Itagaki teaches (“the object of the present invention can also be achieved by providing a storage medium storing program codes for performing the aforesaid processes to a computer system or apparatus (e.g., a personal computer), reading the program codes, by a CPU or MPU of the computer system or apparatus, from the storage medium, then executing the program.” [0171] “A computer program product stored on a computer readable medium comprising a method of evaluating an image forming apparatus” claim 1) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Itagaki into Chatterjee, in order to determine the color matching precision.
25. Claim 16 is similar in scope to the combination of claims 1 and 2, and thus is rejected under similar rationale.
Conclusion
26. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michelle Chin whose telephone number is (571)270-3697. The examiner can normally be reached on Monday-Friday 8:00 AM-4:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Kent Chang can be reached on (571)272-7667. The fax phone number for the organization where this application or proceeding is assigned is (571)273-8300.
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/MICHELLE CHIN/
Primary Examiner, Art Unit 2614
Prosecution Insights