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 .
Status of the Claims
Claims 1, 3-17, and 20-23 are currently pending in the present application, with claims 1 and 21 being independent.
Response to Arguments / Amendments
Applicant’s arguments, see Pg. 1-2, filed 05/13/2026, with respect to the rejection(s) of claim(s) 1, 3-17, and 20-23 under 35 U.S.C. § 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, applicant’s amendments to the claims necessitate a new ground(s) of rejection is made in view of newly found prior art.
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.
Claim 1, 3-17, and 20-23 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.
The term “closely resembles” in claims 1 and 21 is a relative term which renders the claim indefinite. The term “closely resembles” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
It is unclear what constitutes a “spatial frequency profile characteristic that closely resembles a natural outdoor environment.” In particular, it’s not clearly defined what characteristics of the environment are required to be matched, what degree of resemblance is required by the phrase “closely resembles,” whether the resemblance pertains to the entire spatial frequency profile or merely certain portions, and how the claimed “modified data text” itself creates the recited environmental profile.
Additionally, the specification describes modifying the spatial spectrum of text such that resulting spectrum may “resemble the natural outdoor world” and discusses examples involving a 1/f spectrum, background noise, and preservation of readability (fix to quote exact citation). However, the claims do not recite objective boundaries or measurable criteria corresponding to the recited resemblance. The claim language creates uncertainty as to whether the spatial frequency profile is derived from the readable text itself, a displayed background, a combine image, or a reference profile. Accordingly, one of ordinary skill in the art would not be reasonably certain of the scope of the invention. The examiner respectfully requests the applicant to clarify the scope of the claimed invention.
Applicant may overcome the indefiniteness of the claim by amending the claim to more particularly define the spatial frequency profile and the manner in which the profile is determined or compared. For example, the claim may recite objective spectral characteristics, statistical parameters, or defined spatial frequency relationships associated with the modified text rather than the relative phrase.
Claims depending thereon are also rejected for substantially similar reasons as that set forth for the claims from which they depend on.
Claims 1, 3-17, and 20-23 will be examined as best understood by the examiner.
Claim Rejections - 35 USC § 103
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.
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.
Claim(s) 1, 3-4, 8, 11, 14, and 20-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, and further in view of Flitcroft et al. “The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development.” Invest. Ophthalmol. Vis. Sci. 2019;60(9):6452, https://iovs.arvojournals.org/article.aspx?articleid=2747052, hereinafter referred to as “Flitcroft”.
Regarding claim 1, Lawton discloses a computer implemented method to modify the appearance of a readable text, said method comprising the steps of:
obtaining a data text to be adjusted wherein the data text is representative of a readable text (Section 1; study examines filtering text. Section 2.3.4; words were magnified and then filtered),
selecting a filtering model and one or more filtering parameters (Section 2.3.3; the weights for the image enhancement filter were determined from low vision observer's CSF, the normalizing CSF, and a gain factor that determined the maximum amount of enhancement…),
applying a spatial transformation to the data text according to the selected filtering model and filtering parameters (Section 2.3.4.; words were magnified and then filtered…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter) to generate a modified data text having a different spatial contrast characteristic (Section 4; different image enhancement filters as the spatial frequency varied for one observer is plotted in Fig. 2),
and outputting the modified data text as a readable text (Section 2.3.4.; The inverse Fourier transform was computed to transform the filtered words back into the spatial domain for testing reading performance. Sample filtered and unfiltered words have been presented).
Lawton does not disclose selecting a filtering model and one or more filtering parameters dependent on an analysis of said data text, and wherein the modified data text is generated by altering spatial frequency information in the text to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment.
In the same art of text modification systems, Chang discloses selecting a filtering model and one or more filtering parameters (Column 9, lines 49-52; The filter engine 215 determines the filter by maximizing the similarity measure p(S,R) while constraining the mag-nitude of the kth frequency component of the filtered signal R(f)) dependent on an analysis of said data text (Column 11, lines 57-63; the amount of text recognized by the OCR engine may be used to adjust parameters of the filter),
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification method as taught by Lawton with selecting a filtering model and parameters based on an analysis of data text as taught by Change. The motivation lies in the advantage of enabling the filtering model and parameters to be dynamically adapted based on specific text and further optimizing filter performance. The combination yields predictable results in improving text readability under varying conditions data.
Lawton in view of Chang does not disclose wherein the modified data text is generated by altering spatial frequency information in the text to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment.
In the same art of spatial frequencies, Flitcroft discloses to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment (Slide 1-2 and Methods; These images were then analyzed to generate rotationally averaged spatial frequency spectra, and the slope of the log amplitude vs log spatial frequency relationship (SF slope) calculated for each image. Scene luminance in cd/m2 was estimated for each image from camera exposure and aperture settings…Conclusions; Compared to natural outdoor environments, urban outdoor and indoor environments have spatial frequency characteristics that are similar to slightly defocussed (blurred) images, equivalent to 0.66 to 1.51 D. These findings may help to explain the apparent myopigenic nature of the urban and indoor environments).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification method as taught by Lawton in view of Chang with altering spatial frequency techniques based on natural outdoor environment as taught by Flitcroft. The motivation lies in the advantage of using known spatial frequency profiles from natural outdoor environments to enhance readability and overall visualization for text display.
Examiner’s note: Flitcroft is not relied upon for teaching a text-modification pipeline, but rather for teaching that natural outdoor environments exhibit characteristic spatial frequency distributions that affect visual perception. Lawton expressly discloses modifying readable text by performing frequency-domain analysis and spatial filtering to alter spatial frequency content of text (Lawton Section 2.3.4.; words were magnified and then filtered…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter. Section 4; different image enhancement filters as the spatial frequency varied for one observer is plotted in Fig. 2). A person of ordinary skill in the art would have been motivated to configure Lawton’s frequency-domain filtering system using Flitcroft’s derived outdoor spatial frequency characteristics as a design target or reference profile, because Lawton’s system is explicitly capable of modifying text toward any desired frequency distribution. The output modified text whose spatial frequency profile more closely resembles that of a natural environment using known spatial frequency characteristics from one visual domain as a target for shaping signals in another domain is a routine and predictable enhancement in signal and image processing, and does not require Flitcroft to directly modify text itself. Applicant’s reliance on alternative implementations discussed by Flitcroft (e.g., lighting or environmental exposure) does not teach away from text-based modification, as Flitcroft identifies the spectral composition as a relevant factor in visual perception. Accordingly, the examiner maintains that it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine Lawton’s frequency-domain text modification system with the spatial frequency characteristics of natural outdoor environments as taught by Flitcroft.
Regarding claim 3, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and further discloses comprising the step of adjusting the spatial frequency spectrum of the data text towards a desired spectrum using a spatial filter (Lawton Section 4, Par. 4; These filters implement image enhancement by spatial filtering with a constant factor, 1/Gain^2, that serves as an indication of background noise-to-signal ratio).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 1.
Regarding claim 4, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and further discloses wherein the spatial filter is a bandpass or a narrow band filter (Lawton Section 4, Par. 2; the image enhancement filtering functions boost the amplitude of spatial frequencies that are less visible for the low vision observer. This amounts to bandpass filtering with intermediate spatial frequencies being enhanced more than lower spatial frequencies).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 1.
Regarding claim 8, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and further discloses filtering the text data in the spatial domain using a Fourier transform, and applying a filter mask is created which is then multiplied with a two- dimensional FFT amplitude spectrum (Lawton Section 2.3.4.; A two-dimensional fast Fourier transform was used to characterize each size word in the spatial frequency domain. Words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter. A two-dimensional compensation filter was constructed by assuming that an observer's contrast sensitivities at different orientations were approximately equal. Thus, the contrast variation along horizontal and vertical meridians are equal. Image enhancement was implemented using the following computation: (Fourier transform of 5-letter word) x H(f)).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 1.
Regarding claim 11, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and further discloses wherein the spatial transformation comprises an attenuation scaling parameter, wherein a minimum scaling parameter results in no spatial transformation, and a maximum scaling parameter results in complete spatial optimization (Lawton Section 2.3.3-2.3.4; The weights for the image enhancement filter were determined from the low vision observer's CSF, the normalizing CSF, and a gain factor that determined the maximum amount of enhancement… The amount of enhancement for very low and high spatial frequencies was determined by the observer's normalized sensitivity to the lowest and highest spatial frequencies that were visible…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 1.
Regarding claim 14, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 3, and further discloses measuring a viewing distance by a device on which the text is presented and adjusting the parameters of the spatial filter based on the measured viewing distance (Lawton Section 2.3.4; Words were magnified and then filtered, to take into account the observer's viewing distance).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 1.
Regarding claim 20, Lawton in view of Chang and in further view of Flitcroft discloses the computer-implemented method of claim 1, but Lawton in view of Chang does not disclose wherein the modified data text is generated by altering spatial frequency information in the readable text to create a spatial frequency profile characteristic that reduces or eliminates ocular growth response that leads to myopia development.
In the same art of spatial frequencies, Flitcroft discloses wherein the modified data text is generated by altering spatial frequency information in the readable text to create a spatial frequency profile characteristic that reduces or eliminates ocular growth response that leads to myopia development (Slide 1-2 and Methods; These images were then analyzed to generate rotationally averaged spatial frequency spectra, and the slope of the log amplitude vs log spatial frequency relationship (SF slope) calculated for each image. Scene luminance in cd/m2 was estimated for each image from camera exposure and aperture settings…Conclusions; Compared to natural outdoor environments, urban outdoor and indoor environments have spatial frequency characteristics that are similar to slightly defocussed (blurred) images, equivalent to 0.66 to 1.51 D. These findings may help to explain the apparent myopigenic nature of the urban and indoor environments).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification method as taught by Lawton and Chang with altering spatial frequency techniques based on myopia development as taught by Flitcroft. The motivation lies in the advantage of applying spatial frequency modification known to influence ocular growth to text. The combination yields predictable results in reducing the risk of myopia development while maintaining readability.
Regarding claim 21, Lawton discloses a computer system or device, configured to modify the appearance of a readable text, comprising:
a memory;
a processor electrically coupled to the memory and configured to execute instructions received from the memory (Section 2.2 Apparatus); and wherein the processor is further configured to:
obtain a data text to be adjusted wherein the data text is representative of a readable text (Section 1; study examines filtering text. Section 2.3.4; words were magnified and then filtered);
select a filtering model and one or more filtering parameters (Section 2.3.3; the weights for the image enhancement filter were determined from low vision observer's CSF, the normalizing CSF, and a gain factor that determined the maximum amount of enhancement…),
apply a spatial transformation to the data text according to the selected filtering model and filtering parameters (Section 2.3.4.; words were magnified and then filtered…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter)to generate a modified data text having a different spatial contrast characteristic (Section 4; different image enhancement filters as the spatial frequency varied for one observer is plotted in Fig. 2),
and output the modified data text as a readable text (Section 2.3.4.; The inverse Fourier transform was computed to transform the filtered words back into the spatial domain for testing reading performance. Sample filtered and unfiltered words have been presented) to a display screen or printing device (Abstract; enhance the text displayed on Closed-Circuit TVs (CCTVs). Section 2.2; video monitor using a VAX 750 computer),
Lawton does not disclose selecting a filtering model and one or more filtering parameters dependent on an analysis of said data text, and wherein the modified data text is generated by altering spatial frequency information in the text to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment.
In the same art of text modification systems, Chang discloses selecting a filtering model and one or more filtering parameters (Column 9, lines 49-52; The filter engine 215 determines the filter by maximizing the similarity measure p(S,R) while constraining the mag-nitude of the kth frequency component of the filtered signal R(f)) dependent on an analysis of said data text (Column 11, lines 57-63; the amount of text recognized by the OCR engine may be used to adjust parameters of the filter),
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification method as taught by Lawton with selecting a filtering model and parameters based on an analysis of data text as taught by Change. The motivation lies in the advantage of enabling the filtering model and parameters to be dynamically adapted based on specific text and further optimizing filter performance. The combination yields predictable results in improving text readability under varying conditions data.
Lawton in view of Chang does not disclose wherein the modified data text is generated by altering spatial frequency information in the text to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment.
In the same art of spatial frequencies, Flitcroft discloses to create a spatial frequency profile characteristic that closely resembles a natural outdoor environment (Slide 1-2 and Methods; These images were then analyzed to generate rotationally averaged spatial frequency spectra, and the slope of the log amplitude vs log spatial frequency relationship (SF slope) calculated for each image. Scene luminance in cd/m2 was estimated for each image from camera exposure and aperture settings…Conclusions; Compared to natural outdoor environments, urban outdoor and indoor environments have spatial frequency characteristics that are similar to slightly defocussed (blurred) images, equivalent to 0.66 to 1.51 D. These findings may help to explain the apparent myopigenic nature of the urban and indoor environments).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification method as taught by Lawton in view of Chang with altering spatial frequency techniques based on natural outdoor environment as taught by Flitcroft. The motivation lies in the advantage of using known spatial frequency profiles from natural outdoor environments to enhance readability and overall visualization for text display.
Examiner’s note: Flitcroft is not relied upon for teaching a text-modification pipeline, but rather for teaching that natural outdoor environments exhibit characteristic spatial frequency distributions that affect visual perception. Lawton expressly discloses modifying readable text by performing frequency-domain analysis and spatial filtering to alter spatial frequency content of text (Lawton Section 2.3.4.; words were magnified and then filtered…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter. Section 4; different image enhancement filters as the spatial frequency varied for one observer is plotted in Fig. 2). A person of ordinary skill in the art would have been motivated to configure Lawton’s frequency-domain filtering system using Flitcroft’s derived outdoor spatial frequency characteristics as a design target or reference profile, because Lawton’s system is explicitly capable of modifying text toward any desired frequency distribution. The output modified text whose spatial frequency profile more closely resembles that of a natural environment using known spatial frequency characteristics from one visual domain as a target for shaping signals in another domain is a routine and predictable enhancement in signal and image processing, and does not require Flitcroft to directly modify text itself. Applicant’s reliance on alternative implementations discussed by Flitcroft (e.g., lighting or environmental exposure) does not teach away from text-based modification, as Flitcroft identifies the spectral composition as a relevant factor in visual perception. Accordingly, the examiner maintains that it would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine Lawton’s frequency-domain text modification system with the spatial frequency characteristics of natural outdoor environments as taught by Flitcroft.
Regarding claim 22, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, but Lawton in view of Chang does not disclose wherein a spatial frequency profile characteristic that closely resembles a natural outdoor environment is one whose statistical properties fall within a confidence interval derived from a reference set of spatial frequency profiles of natural outdoor images.
In the same art of spatial frequency, Flitcroft discloses wherein a spatial frequency profile characteristic that closely resembles a natural outdoor environment is one whose statistical properties fall within a confidence interval derived from a reference set of spatial frequency profiles of natural outdoor images (Slide 1-2 and Results; The natural images conformed to the well-recognised 1/f relationship in terms of spatial frequency with an SF slope of -1.06 (S.E.: 0.015). The images from outdoor urban and indoor environments all had significantly steeper slopes than the natural outdoors image set (Figs. 1 & 2)…Across all images there was also a significant relationship between estimated log luminance and SF slope (r2=0.25,95%CI 0.039 0.065)… Compared to natural outdoor environments, urban outdoor and indoor environments have spatial frequency characteristics that are similar to slightly defocussed (blurred) images, equivalent to 0.66 to 1.51 D. These findings may help to explain the apparent myopigenic nature of the urban and indoor environments).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text-filtering technique as taught by Lawton in view of Chang with Flitcroft’s statistical characterization of spatial frequency profiles of natural outdoor environments. Doing so provides a common technique of using reference data to validate modified data, by using known outdoor image statistics as a clear reference range for guiding how much text should be adjusted, ensuring modified text reliably matches the spatial frequency characteristics of a natural environment.
Regarding claim 23, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and Lawton further discloses wherein the spatial transformation comprises an attenuation scaling parameter, wherein a minimum scaling parameter results in no spatial transformation, and a maximum scaling parameter results in complete spatial optimization (Lawton Section 2.3.3-2.3.4; The weights for the image enhancement filter were determined from the low vision observer's CSF, the normalizing CSF, and a gain factor that determined the maximum amount of enhancement… The amount of enhancement for very low and high spatial frequencies was determined by the observer's normalized sensitivity to the lowest and highest spatial frequencies that were visible…words were filtered in the spatial frequency domain by multiplying the Fourier transform of each word times each compensation filter).
Lawton in view of Chang does not disclose and wherein a value of the attenuation scaling parameter is chosen to ensure the modified data text closely resembles a natural outdoor environment, and wherein a spatial frequency profile characteristic that closely resembles a natural outdoor environment is one whose statistical properties fall within a confidence interval derived from a reference set of spatial frequency profiles of natural outdoor images.
In the same art of spatial frequency, Flitcroft discloses wherein a value of the attenuation scaling parameter is chosen to ensure the modified data text closely resembles a natural outdoor environment, and wherein a spatial frequency profile characteristic that closely resembles a natural outdoor environment is one whose statistical properties fall within a confidence interval derived from a reference set of spatial frequency profiles of natural outdoor images (Slide 1-2 and Results; The natural images conformed to the well-recognised 1/f relationship in terms of spatial frequency with an SF slope of -1.06 (S.E.: 0.015). The images from outdoor urban and indoor environments all had significantly steeper slopes than the natural outdoors image set (Figs. 1 & 2)…Across all images there was also a significant relationship between estimated log luminance and SF slope (r2=0.25,95%CI 0.039 0.065)… Compared to natural outdoor environments, urban outdoor and indoor environments have spatial frequency characteristics that are similar to slightly defocussed (blurred) images, equivalent to 0.66 to 1.51 D. These findings may help to explain the apparent myopigenic nature of the urban and indoor environments).
Lawton, Chang, and Flitcroft are combined for the reason set forth above with respect to claim 22.
Claim(s) 5 and 6 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and further in view of Bex et al., "Spatial frequency, phase, and the contrast of natural images," J. Opt. Soc. Am. A 19, 1096-1106 (2002), hereinafter referred to as “Bex”.
Regarding claim 5, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 3, but does not disclose wherein, spectral properties of the spatial filter can be calculated from the contrast ratio of text to an ideal spectrum.
In the same art of spatial frequency, Bex discloses wherein, spectral properties of the spatial filter can be calculated from the contrast ratio (Pg. 1102, Section 5; measured the contribution of structure at different spatial frequencies to the threshold and suprathreshold apparent contrast of a random selection of a set of natural images whose spatial-frequency spectrum is complex) of text to an ideal spectrum (see Section 1B-1C on spatial-frequency spectrum and contrast of natural images).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the spectral filtering method of Lawton, Chang, and Flitcroft with calculating spectral properties from the contrast ratio of text to an ideal spectrum as taught by Bex. The motivation lies in the advantage of enabling precise and targeted adjustment of spatial frequency by deriving filter characteristics directly from a measurable comparison to an ideal spectrum, yielding predictable results in improving text visibility.
Regarding claim 6, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, but does not disclose comprising the steps of: using a low-pass filter with a contrast ratio data, and creating a model which fits the shape of a contrast ratio curve over a selected range of spatial frequencies for visual reading.
In the same art of spatial frequency, Bex discloses comprising the steps of: using a low-pass filter (Pg. 1097, Section 1C; low-pass-filtered version of the image) with a contrast ratio data (Pg. 1097, Section 1C and Formulas (2)-(5); CM is based on the most and the least intense points in the image…Crms is the standard deviation of luminance values…another contrast metric, band-limited contrast (Cbl) represents an attempt to take account of the intensity of a point in an image and the local mean luminance at that point by computing a quantity that can be called the local contrast, CL) and creating a model (Pg. 1102; Fig. 5-6) which fits the shape of a contrast ratio curve over a selected range of spatial frequencies for visual reading (Pg. 1101-1102, Section 4C; To facilitate comparison between the data for contrast matching and contrast detection, we have plotted the inverse of the relative matching contrasts…Cbl can predict an increase or a decrease in apparent contrast, depending on the spatial frequencies of the low-pass and bandpass image selected).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the filtering approach as taught by Lawton, Chang, and Flitcroft with the low-pass filter and contrast ratio data to create a model that fits a contrast ratio curve as taught by Bex. Doing so would allow a user to tailor the filter profile to match human visual performance, yielding predictable results in improved readability.
Claim(s) 7 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and in further view of Marks et al. (US 20070057950), hereinafter referred to as “Marks”.
Regarding claim 7, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, but does not disclose comprising the step of analyzing the readable text for a particular font and comparing fonts in terms of their frequency spectrum and applying the spatial transformation based on the particular font.
In the same art of text modification systems, Marks discloses comprising the step of analyzing the readable text for a particular font and comparing fonts (Par. 0023; the degree to which font smoothing is useful for a given font size varies in accordance with which font is selected…Par. 0026; the text has attributes that specify the font in which the text is to be rendered.) in terms of their frequency spectrum and applying the spatial transformation based on the particular font (Par. 0033; the height of the text is determined. The height of the text run conveys the level of spatial frequencies of text as the text will actually appear in the rendering surface).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification system as taught by Lawton, Chang, and Flitcroft with the analyzation technique based on particular fonts as taught by Marks. The motivation lies in the advantage of improving rendering accuracy by incorporating font-specific properties of text, yielding predictable results in enhancing text readability and optimizing the transformation for the intended text appearance. The combination would also improve overall text analysis and modification efficiency by allowing the system to pre-determine optimal processing parameters for different fonts, reducing computation overhead while still maintaining consistent readability.
Regarding claim 16, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, and further discloses spatial filtering applied (Lawton Section 4; These filters implement image enhancement by spatial filtering).
However, Lawton in view of Chang and in further view of Flitcroft does not disclose wherein a spatial frequency profile of a specific text font is analyzed, and a modified text font is stored for later use, or output to a display screen, viewing device or printing device.
In the same art of text modification systems, Marks discloses wherein a spatial frequency profile (Par. 0033; The height of the text run conveys the level of spatial frequencies of text as the text will actually appear in the rendering surface) of a specific text font is analyzed (Par. 0023; the degree to which font smoothing is useful for a given font size varies in accordance with which font is selected. Par. 0026; the text has attributes that specify the font in which the text is to be rendered), and a modified text font (Fig. 2 exemplary flow for size-based font smoothing) is stored for later use (Par. 0006; a computer-implemented system includes a document that is configured to receive and store text to be rendered…), or output to a display screen, viewing device or printing device (Par. 0018-0020; Document 110 is any document that comprises text (such as characters, numbers, symbols, ideographs, diacritical markings, and the like) for rendering (including displaying, printing, and the like)…Rendering surface 150 is a surface, such as provided by a printer or a screen).
Lawton in view of Chang and Marks are combined for the reason set forth above with respect to claim 7.
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and further in view of Langlois et al. (US 20210118110), hereinafter referred to as “Langlois”.
Regarding claim 9, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 8, and further discloses profiles of the required filter masks (Lawton Section 2.3.4; A two-dimensional compensation filter was constructed) are created from either the filtered contrast ratio curve or a model (Lawton Section 2.3.4; The contrast variation along horizontal and vertical meridians are equal. Section 4 and Fig. 2; The gain of these different image enhancement filters as the spatial frequency is varied for one observer is plotted in Fig. 2).
Lawton in view of Chang does not disclose wherein a zero frequency point is shifted to the center of a FFT matrix.
In the same art of discrete and fast Fourier transform, Langlois discloses wherein a zero frequency point is shifted to the center of a FFT matrix (Par. 0350; FIG. 19, depicting matrices with even (1910) and odd (1920) values of N, to illustrate the symmetries in the Fourier space. These images in the frequency domain are represented by N×N matrices. The top row and left column of both matrices 1910 and 1920 are referred to as the DC row and DC column, corresponding to the zero or DC frequency components. In contrast to these corner-shifted matrices of values, plots in the frequency domain typically show the zero or DC frequency at the center of a circle. Par. 0388; high frequency components are positioned closer to the center of the two-dimensional spectrum…).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification system of Lawton, Chang and Flitcroft with the FFT matrix processing as taught by Langlois, since it is known for the zero-point frequency point being shifted to the center of the FFT matrix. Shifting the DC (zero frequency) component to the center of the FFT matrix is a routine step in 2D FFT-based image filtering, as recognized in the image processing art. The motivation to combine lies in the advantage of practical filter mask design and application, allowing the filter profile to be more aligned with low and high spatial frequency regions. The combination yields predictable result as standard zero-frequency centering is a well-known routine practice, a standard pre-processing step in 2D FFT-based image filtering, and provides for easier interpretation (Langlois; Par. 0388; Application of Fast Fourier Transform (FFT) to image data in spatial domain results in corner shifted spectrum in which amplitudes of low frequency components end up at the corners of the two-dimensional spectrum in Fourier space (or frequency domain)…For ease of understanding, it is useful to visualize the frequency content in frequency domain as center shifted spectrum…corner shifted spectrum can be converted to center shifted spectrum in a straightforward manner and vice versa...The center shifted spectrum in FIG. 18 is presented for ease of understanding of the reader).
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and further in view of Tyulyaev et al. (US 20200387553), hereinafter referred to as "Tyulyaev".
Regarding claim 10, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, but does not disclose the step of adjusting the confidence interval of the modified data text so that the amount of adjustment of the spatial transformation is controlled.
In the same art of document image processing, Tyulyaev discloses the step of adjusting the confidence interval of the modified data text so that the amount of adjustment of the spatial transformation is controlled (Par. 0111; a confidence score that indicates a confident in accurately identifying spatial coordinates for a shape or text, and/or the like).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification system as taught by Lawton, Chang, and Flitcroft with adjusting processing parameters based on confidence scores as taught by Tyulyaev. The motivation lies in the advantage of dynamically controlling the degree of transformation according to the confidence in text analysis, reducing unnecessary computation. The incorporation of confidence values is a well-known technique in the art, yielding predictable results in improved accuracy and efficiency in visual modifications.
Claim(s) 12 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and further in view of Hess et al., (WO 2020146952), hereinafter referred to as "Hess".
Regarding claim 12, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 3, but does not disclose wherein the spatial filter is a symmetrical function on a log axis and fitted by a log-gaussian model.
In the same art of spatial frequencies, Hess discloses wherein the spatial filter (Par. 0035; spatially filtered dot element) is a symmetrical function (Fig. 3b) on a log axis and fitted by a log-gaussian model (Par. 0036; The spatial frequency spectrum is Gaussian on a log-frequency axis. Par. 0041; a log-transform may be performed on the frequency axis and the amplitude spectrum may be defined as a Gaussian on that log-frequency axis).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the spatial filtering approach as taught by Lawton, Chang, and Flitcroft with the use of a symmetrical spatial filter on a log axis fitted by a log-Gaussian model as taught by Hess. This is a well-known technique in the art of spatial frequency analysis for modeling filter responses that reflect human visual sensitivity across frequencies. The motivation lies in the advantage of allowing smoother and accurate filtering, further improving overall readability.
Regarding claim 13, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 3, but does not disclose wherein the spatial filter is a logGabor function configured to create a set of orientation and band-pass frequency filters to allow for orientation specific spatial filtering.
In the same art of spatial frequencies, Hess discloses wherein the spatial filter (Par. 0035; spatially filtered dot element) is a logGabor function (Figures 3A-3B and 8A-8C illustrate log-Gabor dots) configured to create a set of orientation and band-pass frequency filters to allow for orientation specific spatial filtering (Par. 0036; bandpass log-Gabor dots…Par. 0039; The bandpass spatial frequency spectrum may be obviously seen in Figure 3B…and a bandpass filter may include both a high-pass filter and a low-pass filter…).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the spatial filtering approach as taught by Lawton, Chang, and Flitcroft with a logGabor function for orientation-specific band-pass filtering. The motivation lies in the advantage of enhancing relevant orientation features in textual analysis, while reducing interference from unrelated spatial frequencies, yielding predictable results in improving effectiveness of filtering processes.
Claim(s) 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and further in view of Ratliff et al. "Retina is structured to process an excess of darkness in natural scenes", 05 October 2010 (2010-10-05), Vol. 107, No. 40, pages 17368-17373, hereinafter referred to as “Ratliff”.
Regarding claim 15, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 3, but does not disclose wherein the spatial filtering of the text is calculated to increase the simulation of ON-center retinal cells and decrease the stimulation of OFF-center retinal cells.
In the same art of spatial filtering, Ratliff discloses wherein the spatial filtering of the text is calculated to increase the simulation of ON-center retinal cells and decrease the stimulation of OFF-center retinal cells (Results and Fig. 1; (B); OFF dendritic arbors are smaller but more densely branches. ON and OFF ganglion cels (brisk-transient class) in flat view are shown. Fig. 2; (B) Image rectified into separate channels for positive (ON) and negative (OFF)).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the spatial filtering approach as taught by Lawton, Chang, and Flitcroft with adjusting spatial filtering based on stimulation of ON-centre and OFF-centre retinal cells. The motivation lies in the advantage of using biological visual responses as a guide for filtering processes. This allows the system to emphasize spatial frequencies that improve perceived contrast while reducing those that may contribute to reduced clarity, yielding predictable results in optimizing text appearance for visual reading.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lawton "Image enhancement filters in CCTVs significantly improve reading performance for low-vision observers", ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX - PROCEEDINGS OF SPIE, Vol. 1644, 14 August 1992 (1992-08-14), pages 254-264, in view of Chang et al. (US 10657369), hereinafter referred to as “Chang”, in further view of Flitcroft "The Spatial Frequency Content of Urban and Indoor Environments as a Potential Risk Factor for Myopia Development", INVESTIGATIVE OPTHALMOLOGY & VISUAL SCIENCE,Vol. 61, No. 11, 28 September 2020 (2020-09-28), Article 42, pages 1-10, and in further view of Yamakado et al. (US 20070065012), hereinafter referred to as “Yamakado”.
Regarding claim 17, Lawton in view of Chang and in further view of Flitcroft discloses the computer implemented method of claim 1, but does not disclose wherein a spatial frequency profile of the text is modified by the addition of a background texture or pattern.
In the same art of frequency characteristics of text, Yamakado discloses wherein a spatial frequency profile of the text (feature frequency of the character image) is modified by the addition of a background texture or pattern (Fig. 4 and Par. 0008; extracts from the processing target area a background feature parameter that includes a feature frequency showing a frequency characteristics of the processing target area…a combination of the background feature parameter and the character feature parameter; and an image processor that performs image processing on the processing target area in accordance with the parameter determined).
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention, to combine the text modification system as taught by Lawton, Chang, and Flitcroftwith spatial frequency profile of the text modified by the addition of a background texture or pattern as taught by Yamakado. The motivation lies in the advantage of using background elements to influence spatial frequency characteristics of the text. The use of separate foreground and background elements being used for image processing is a well-known technique in the art, further yielding predictable results in improving contrast and visual distinction for better readability.
Conclusion
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/JENNY N TRAN/Examiner, Art Unit 2615
/TAMMY GODDARD/Supervisory Patent Examiner, Art Unit 2611
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