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 .
Claim Status
Claims 1-14 are pending for examination in the Application No. 18/623,305 filed April 1st, 2024. In the remarks and amendments received on June 17th, 2026, claims 1 and 6-9 are amended and claims 2 and 10 are canceled. Accordingly, claims 1-14 are currently pending for examination in the application.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed as Patent Application No. JP2023-060425, filed on April 3rd, 2023.
Response to Amendment
Applicant’s amendments filed June 17th, 2026, to the Specification and Claims have overcome each and every objection previously set forth in the Non-Final Office Action mailed May 12th, 2026. Accordingly, the objection(s) are withdrawn in response to the remarks and amendments filed. Examiner warmly thanks Applicant for considering the suggested amendments to be made to the disclosure.
Response to Arguments
Applicant’s arguments filed June 17th, 2026, regarding the rejection(s) of the independent claim(s) have been fully considered but are not persuasive.
Applicant’s Remarks Regarding Independent Claims 1, 8, and 9
The examiner respectfully disagrees with Applicant's assertion that Suzuki does not disclose “teaching the feature of correcting an attention region located at a background region" because Suzuki discloses "merely ask[ing] whether a single target pixel is 'not foreground' ” and that determining an attention region is “not a foreground pixel” is not definite that the attention region is a background pixel (pgs. 2-3 of Applicant's Remarks).
As detailed in the current rejection below, Suzuki discloses that solving the problem of show-through images comprises classifying regions of an image into foreground and background regions (see para. [0010]: "background image and foreground image are separated... and the background image region is selectively corrected") and that regions are detected as background regions (see para. [0029]: pixels are determined as part of "background image detection"). Therefore, a region determined as "not a foreground pixel" is determining the region is at least a background region.
Furthermore, the examiner disagrees with Applicant's remark that Sawada “does not teach regional-level correction prompted by an affirmative determination of a background attention region” (pg. 3 of Applicant's Remarks). The examiner respectfully notes that Sawada is brought-in to merely teach determining the claim limitation “whether, from among the plurality of regions, an attention region and each of a plurality of reference regions located around the attention region are similar based on a difference between a color component of the attention region and a color component of a corresponding one of the plurality of reference regions”, where Suzuki primarily discloses said regional-level correction prompted by an affirmative determination of a background attention region (see the rejection of the claim limitation in the rejection of claim 1 below).
The examiner respectfully disagrees with Applicant's assertion that one of ordinary skill in the art would not be motivated to modify Suzuki with Kanbara to teach the features of claim 2 of determining that “an image reference region has an identical background to an attention region for show-through removal” because Suzuki and Kanbara address “materially different problem[s]” and target pixel correction processes that contrast each other (pgs. 3-4 of Applicant's Remarks).
Although Suzuki and Kanbara address two different problems within their respective disclosures, both authors address the same problem in the same field of endeavor of correcting attention regions in an image (i.e., target pixels) using reference regions determined to have identical backgrounds to the attention regions (see the rejection of claim 1 below).
Further, said correction related to said identical background identification being addressed by the features of claim 2 as currently claimed in the independent claims do not relate to the correction method being disclosed by Suzuki for show-through correction as claimed previously in the claim limitation “correct... the attention region using one of the plurality of regions determined to be similar to the attention region” as recited in the independent claims. Therefore, the teachings of Kanbara do not contradict with the process of Suzuki as the features of claim 2 merely require correcting an attention region in an image and do not require performing said correction "for show-through correction" as remarked by Applicant.
The examiner respectfully disagrees that “none of the cited references teaches correct[ing] an attention region by utilizing the background of a reference region that is determined to be identical as the attention region” because Suzuki and Kanbara “does not determine that the target pixel and each reference region have an identical background” (pgs. 4-5 of Applicant's Remarks).
An “identical background” as currently claimed does not preclude the interpretation set forth by Suzuki and Kanbara of regions sharing the same (i.e., “identical”) classification as being a background region of an image. Therefore, since Suzuki discloses determining reference regions classified as background regions (see para. [0029]: “Pixels within a set reference range that are not part of the front-print content”) share the same background region classification to an attention region (see para. [0029]: "target pixel that is subject to background image detection and processing"), the reference regions and attention region have identical backgrounds. Similarly, Kanbara teaches an attention region and a reference region having identical backgrounds as regions sharing the same background classification (e.g., see para. [0029]: regions with same luminance such as "crushed shadows").
The examiner respectfully disagrees that “none of the cited references teaches correct[ing] an attention region by utilizing the background of a reference region that is determined to be identical as the attention region” because Sawada “registers candidate colors for divided areas and selects a closest candidate color for a target pixel based on color value relationships, not based on whether surrounding reference regions share an identical background with an attention region” (pgs. 4-5 of Applicant's Remarks).
Para. [0074] of Applicant's instant Specification recites that “identical reference regions” include a “region determined to be similar to the attention region”. Therefore, an “identical background” as currently recited in the claims does not preclude Sawada's interpretation that a region with a "closest candidate color" to the attention region can be “background region[s]”, such as similarly recited in para. [0074] of Applicant's instant Specification.
Applicant’s Remarks Regarding Dependent Claim 6
The examiner respectfully disagrees with Applicant's assertion that “none of [the] cited references teaches or suggests the amended limitations requiring calculation of a first correction color as a brightest color among colors of the plurality of reference regions, calculation of a second correction color darker than thee first correction color, and calculation of the representative color by combining the first correction color and the second correction color at a predetermined ratio” because Sawada “uses brightness/darkness only as a replacement permission safeguard, not as a basis for calculating two correction colors and combining them to generate a representative color”.
As detailed in the rejection of claim 6 below, Sawada teaches the "representative color" as an "average value" of at least a first correction color of a "maximum [luminance] Y value" and a second correction color darker in color than the first correction color (e.g., "minimum [luminance] Y value") at a predetermined ratio--i.e., an "average value" is combining the values of each correction color in a ratio of equal parts (see para(s). [0056] and [0086] and Fig. 14 cited in the rejection of claim 6 below). Further, the amended limitations do not require using said generated “representative color” in any correction processes recited in the claims. Therefore, Sawada teaches said generation of the “representative color” by combining said two correction colors.
Claim Objections
Claims 1, 8, and 9 are objected to because of the following informalities:
In lines 19-25 of claim 1, 17-23 of claim 8, and19-25 of claim 9: the examiner respectfully suggests amending the phrase “the reference regions” to recite “the plurality of reference regions” to maintain consistency in terminology.
Appropriate correction is required.
Claim Interpretation
Additional Claim Interpretations:
Regarding claim(s) 1, 4, 8-9, and 12, each claim recites the term "similar" in regards to between a “plurality of reference regions” and an “attention region” based on “a difference between a color component of the attention region and a color component of a corresponding one of the plurality of reference regions”. The term “similar” is a relative term. The instant specification provides a standard for ascertaining these terms as satisfying a threshold difference between the color components of the plurality of reference regions and the attention region (paragraph [0057-0058]). Therefore, for examination purposes, the term "similar" modifying the claim limitations of between a “plurality of reference regions” and an “attention region” based on “a difference between a color component of the attention region and a color component of a corresponding one of the plurality of reference regions” will be interpreted as the difference between the color components of the “plurality of reference regions” and the “attention region” satisfying a threshold difference value as disclosed in paragraphs [0057-0058] of the instant specification.
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.
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.
Claims 1, 3-9, and 11-14 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki (JP 2004056710 A) in view of Sawada et al. (Sawada; US 2016/0295076 A1), and further in view of Kanbara et al. (Kanbara; US 2019/0066271 A1).
Regarding claim 1, Suzuki discloses an image processing apparatus comprising circuitry configured to:
classify a plurality of regions in an input image into a foreground region containing a foreground image and a background region containing a background image, wherein each of the plurality of the regions comprises one or more pixels (description, para(s). [0010], [0029] and [0051-0053], recite(s)
[0010] “In the invention described in Japanese Patent Publication No. 2001-169080, the background and foreground images are separated mainly by edge information extracted from the input image, and the background region is selectively corrected. …”
[0029] “First, a reference range of a practical size is set around the target pixel that is subject to back-image detection and correction processing. Since this process uses only pixel information within the set reference range, it is consistent with the online process described above. Pixels within a set reference range that are not part of the front-print content are clustered in a specific color space (e.g., RGB color space), and a representative color is extracted from each cluster. …”
[0051] “First, an image of the area around the target pixel is input (step S11). Here, the position of the target pixel in the input image is (i, j), and the following steps S12 to S21 (or steps S14 to S21) should be performed on that target pixel. Assume this position corresponds to the order of a typical raster scan. If the target pixel is a foreground pixel detected at the edge or elsewhere in the front print, the target is updated to the next pixel using raster scanning. If a certain percentage of foreground pixels are included within the reference range, the target pixels will not be corrected, thereby providing more thorough protection for front-facing printing. …”
[0052] “…Front-printed content, such as characters, exhibits strong edge strength, so edges can be extracted (step S12), and threshold processing (step S13) on the edge strength (edge amount) can be used to determine whether or not it is front-printed. …Furthermore, if the characteristics of the scanner are known, foreground pixels can be identified and protected by applying thresholding to the pixel values themselves or the brightness values based on that information. …Pixels identified as being in the foreground will be referred to as foreground pixels below.”
[0053] “If the target is not a foreground pixel, a reference range of a predetermined size is set around the target pixel (step S14), and the pixel values within that reference range are clustered in a specific color space to calculate a representative color (step S15). In its simplest form, this representative color calculation only requires determining the brightest color within this reference range (hereinafter referred to as the brightest color). By replacing the target with this brightest color, a certain degree of back-image correction performance can be obtained. For greater accuracy, it is advisable to use statistical methods such as linear discriminant functions.”
, where foreground images (e.g., “foreground pixel[s]”) are foreground regions and background images (e.g., “not [a] foreground pixel[s]”) are background regions (i.e., “not [a] foreground pixel[s]” is/are background pixel(s) as para. [0019] recites “background… images” and para. [0029] recites such pixels as part of “background image detection”));
extract a brightness component and a color component of each of the plurality of regions (description, para(s). [0052-0053]—see citations previously above—, where para(s). [0029] further recite(s):
[0029] “…Similarly, the method for extracting representative colors from each cluster is also the same; the simplest method is to use the average of the pixel values of the pixels belonging to the cluster, or other statistical measures can be used. If it is necessary to use actual pixel values within the image, this can be substituted by using the pixel value closest to the average value. In the following, we will refer to the color of that pixel as the replacement color and the pixel as the replacement pixel.”
, where determining “brightness values” and “colors” of the plurality of regions (e.g., “pixel[s]” and/or “cluster[s]”) is extracting a brightness component and a color component, respectively, of each of the plurality of regions (e.g., “pixel[s]” and/or “cluster[s]”));
determine(description, para(s). [0029], [0034], and [0054], recite(s)
[0029] “First, a reference range of a practical size is set around the target pixel that is subject to back-image detection and correction processing. Since this process uses only pixel information within the set reference range, it is consistent with the online process described above. Pixels within a set reference range that are not part of the front-print content are clustered in a specific color space (e.g., RGB color space), and a representative color is extracted from each cluster. Any clustering method is acceptable as long as it strikes a good balance between speed and accuracy; for example, a linear discriminant function can be used.”
[0034] “…The position and pixel value of the replacement pixels to be replaced for each target pixel, which are necessary for the back-image correction process shown here, should be determined in the same way as the back-image detection and correction processes described above. The difference in pixel values between the target pixel and the replacement pixel represents the back-image component in the target pixel, and the positional relationship between the two provides information about the shape and size of the back-image region containing the target pixel.”
[0054] “The difference B in pixel value and the difference D in position between the pixel that is the brighter representative color among the calculated representative colors (the brightest pixel in the simplest method described above) and the target pixel are calculated (steps S16, S17). The difference B in pixel values has the same color space dimensions (e.g., RGB) as the input image. The positional difference D contains two-dimensional information. ”
, where determining the replacement color for the “target pixel” include determining a “difference B in pixel” value between the “pixel that is the brighter representative color among the calculated representative colors” of the “reference range” is determining, from among the plurality of regions, an attention region (e.g., “target pixel” region) and each of a plurality of reference regions (e.g., “pixels within a set reference range of a practical size”) located around the attention region (e.g., “set around the target pixel”) based on at least the color component of the attention region (e.g., “pixel value” of the “target pixel”) and a color component of a corresponding one of the plurality of reference regions (e.g., a “pixel value” of the “brighter representative color among the calculated representative colors”));
correct, in response to the attention region being determined to be included in the background region, the attention region using one of the plurality of reference regions(description, para(s). [0051] and [0053]—see citation in the first claim limitation of the current claim above—and para(s). [0054]—see citation in preceding limitation immediately above—, where replacing the “target” pixel is correcting the attention region (e.g., “target” pixel region) using one of the plurality of reference regions (e.g., a “brightest pixel” in the “reference range of a predetermined size [is] set around the target pixel”) in response to the attention region being determined to be included in the background region (e.g., “not a foreground pixel”));
generate a show-through removed image, from which a show-through component of the input image is removed, by sequentially shifting the attention region to a subsequent attention region to correct the shifted attention region (description, para(s). [0031] and [0055-0056], recite(s)
[0031] “…Typically, pixels experiencing bleed-through tend to have lower brightness compared to pixels without bleed-through. Therefore, by comparing the brightness of the representative colors obtained from these two clusters, it is possible to infer which one is the bleed-through. By replacing the target pixel with a high-luminance representative color, the back-image component of the target pixel can be corrected.”
[0055] “…The calculated variable α and the pixel values of the target pixel and the replacement pixel are substituted into equation (1) to obtain the replacement color (pixel value) X that replaces the target pixel (step S19). Finally, the target pixel is replaced with a replacement pixel, and the next pixel is set as the target pixel in a raster scan (step S20).”
[0056] “ By performing the above operations on all pixels of the input image (YES in step S21), it is possible to correct the bleed-through of thin lines while simultaneously correcting broad bleed-through without it looking unnatural. …”
, where “correct[ing] the bleed-through” of the “input image” is generating a show-through removed image including by sequentially shifting (e.g., “raster scan[ning]”) the attention region (e.g., “target pixel” region) to a subsequent attention region (e.g., “next pixel is set as the target pixel” region)); and
determine whether each of the reference regions and the attention region have an identical background (description, para(s). [0053]—see citation in claim limitation “classify a plurality of regions…” above—, where description, para(s). [0029], further recite(s):
[0029] “First, a reference range of a practical size is set around the target pixel that is subject to back-image detection and correction processing. Since this process uses only pixel information within the set reference range, it is consistent with the online process described above. Pixels within a set reference range that are not part of the front-print content are clustered in a specific color space (e.g., RGB color space), and a representative color is extracted from each cluster. Any clustering method is acceptable as long as it strikes a good balance between speed and accuracy; for example, a linear discriminant function can be used. Similarly, the method for extracting representative colors from each cluster is also the same; the simplest method is to use the average of the pixel values of the pixels belonging to the cluster, or other statistical measures can be used. If it is necessary to use actual pixel values within the image, this can be substituted by using the pixel value closest to the average value. In the following, we will refer to the color of that pixel as the replacement color and the pixel as the replacement pixel.”
, where determining the “Pixels within a set reference range that are not part of the front-print content” is determining each reference region having an identical background to the attention region (i.e., the attention region has an identical background to the determined reference regions because para. [0053] discloses that the attention regions—“target pixels”—are also not foreground regions—“not [a] foreground pixel[s]”)),
wherein the circuitry corrects, in response to the attention region being determined to be included in the background region, the attention region using a reference region determined to have the identical background as the attention region (description, para(s). [0053]—see citation in limitation “classify a plurality of regions…” above—, where description, para(s). [0055], further recite(s):
[0055] “…The calculated variable α and the pixel values of the target pixel and the replacement pixel are substituted into equation (1) to obtain the replacement color (pixel value) X that replaces the target pixel (step S19). Finally, the target pixel is replaced with a replacement pixel, and the next pixel is set as the target pixel in a raster scan (step S20).”
, where correcting the attention region (e.g., “target pixel”) by “replac[ing]” the color of the “target pixel” using the “representative color” calculated from the replacement color of a reference region (e.g., a pixel “within a set reference range that are not part of the front-print content are clustered in a specific color space” as previously disclosed in para. [0029] in the current claim above) is correcting the attention region using a reference region determined to have the identical background as the attention region) and located closer to the attention region than a reference region determined(description, para(s). [0029]—see citation in limitation “determine whether each of the reference regions and the attention region have an identical background” above—, where description, para(s). [0041] and [0036,] further recite(s):
[0041] “Here, s is an index representing the size of the back exposure that should be completely corrected, and if the distance D is smaller than s, the target pixel is completely replaced by the replacement pixel. Conversely, if the distance D is greater than the index e, the target pixel is not corrected at all. …”
[0036] “Figure 1 shows an example of a reference range for correcting bleed-through. If it is determined that back exposure has occurred at the target pixel, the positional relationship (hereinafter referred to as distance D) between that target pixel 2 and the replacement pixel is calculated. In the case of bleed-through of thin lines such as letters or ruled lines, this distance D generally takes a small value. In contrast, in the case of wide back exposure, the distance D increases as you move from the peripheral area to the center, and the maximum distance Dmax (see Figure 1) between a pixel within reference range 1 and the target pixel 2 becomes the upper bound.”
, where correcting the “target pixel” includes determining the “replacement pixel” as a pixel in the “reference range” being below a threshold distance (e.g., “distance D is smaller than s”) is the reference region being located closer (e.g., “distance D generally takes a small value”) to the attention region than a reference region determined not to have the identical background as the attention region (e.g., a pixel within the “reference range” that is “part of the front-print content” as disclosed previously in para. [0029] in the current claim above)).
Where Suzuki does not specifically disclose
determine whether, from among the plurality of regions, an attention region and each of a plurality of reference regions …are similar based on a difference between a color component of the attention region and a color component of a corresponding one of the plurality of reference regions; and
correct …the attention region using a reference region determined to be similar to the attention region;
Sawada teaches in the same field of endeavor of correcting input images based on a color component of an attention region and a plurality of reference regions
determine whether, from among the plurality of regions, an attention region and each of a plurality of reference regions …are similar based on a difference between a color component of the attention region and a color component of a corresponding one of the plurality of reference regions (para(s). [0054], [0064], and [0086-0088], recite(s)
[0054] “…As shown in FIG. 7, first, the CPU 21 converts each of the color values (R, G, B) of all the pixels of the original image data to each of the color values in the YCbCr color space, using Expressions (1) to (3) (step S71). Next, the CPU 21 acquires a target block of N×N pixels from the original image data (step S73). The target block acquired at step S73 is, among a plurality of divided blocks included in the original image data, one of unprocessed blocks for which the table generation processing has not been performed. The plurality of divided blocks are a plurality of square-shaped image areas obtained by dividing the original image into block units of N×N pixels in a grid shape.”
[0064] “When it is determined that at least one of the variation amounts (qY/qCb/qCr) is not less than bthresh (no at step S87), the variation of each of the color values of all the pixels in the divided block is relatively small. In this case, the CPU 21 stores the per block average (baveY, baveCb, baveCr) acquired at step S77 in a three-dimensional table 100 (refer to FIG. 11) that is stored in the RAM 23 (step S89).”
[0086] “On the other hand, when the target pixel t2 acquired at step S101 is a pixel of the third attribute (yes at step S107), the CPU 21 acquires dY from an area D2 of 3×3 pixels centered on the target pixel t2 (step S121). In the area D2, one pixel adjacent to the right of the target pixel t2 shows a noise image of read minute dirt, for example. Eight pixels of the nine pixels in the area D2, excluding the aforementioned one pixel, show the base color image read from the sheet. In this case, the Y value of the one pixel showing the noise image is a minimum Y value of the area D2. The maximum value of each of the Y values of the eight pixels showing the base color image is a maximum Y value of the area D2. A difference between the minimum Y value and the maximum Y value in the area D2 (i.e., a luminance difference in the area D2) is relatively small. Accordingly, since dY is less than th2 (yes at step S123), the CPU 21 further performs processing described below.”
[0087] “As shown in FIG. 15, the CPU 21 determines the target color pc (pcY, pcCb, pcCr) that is closest to a color value (tY, tCb, tCr) of the target pixel t2, from among the posterization candidate colors in the three-dimensional table 100 (step S127). The CPU 21 calculates the distance (L2) from the color value of the target pixel t2 to the target color pc (step S129). When L2 is not less than the threshold value (th3) (no at step S131), a color difference between the color value of the target pixel t2 and the target color pc is large. When the color value of the target pixel t2 is replaced by the target color pc, the hue of the target pixel t2 in the original image may deteriorate. …”
[0088] “When L2 is less than the threshold value (th3) (yes at step S131), the CPU 21 calculates the luminance difference (L3) between the Y value “255” of white and the tY value of the target pixel t2 (step S133). When the tY value is equal to or less than “233,” L3 is equal to or more than the threshold value (th4) (no at step S135). The color of the target pixel t2 is not close to white. Therefore, the CPU 21 replaces the color value of the target pixel t2 with the target color pc, and outputs the replaced color value of the target pixel t2 (step S137). …”
, where “determin[ing] the target color… that is closest to a color value… of the target pixel” such that the target color is “not less than” the target pixel color is determining whether an attention region (e.g., “target pixel”) and each of a plurality of reference regions (e.g., “candidate colors”, which are colors determined from at least “an area D2 of …pixels centered on [a] target pixel”) are similar (e.g., “closest”) based on a difference (e.g., “distance (L2)”) of at least between a color component of the attention region (e.g., “color value of the target pixel t2”) and a color component of a corresponding one of the plurality of reference regions (i.e., “target color pc”)); and
correct …the attention region using a reference region determined to be similar to the attention region (para(s). [0092], recite(s)
[0092] “In the processed image data, the color value of a specific pixel included in the pixels of the third attribute has been replaced by the posterization candidate color that is closest to the color value of the specific pixel. Among the pixels of the third attribute, the specific pixel is a pixel having a color value that is not close to white, or a pixel having a luminance that is equal to or more than the luminance of the target color. Thus, the color value of the specific pixel included in the original image data may be replaced by the posterization candidate color that is closest to the color value of the specific pixel. It may be possible to improve the image quality of the original image data while maintaining the hue of the original image.”
, where “replac[ing]” the target pixel with a “posterization candidate color that is closest to the color value” of the target pixel (e.g., “specific pixel”) is correcting the attention region (e.g., “specific pixel included in the pixels of the third attribute”) using a reference region (e.g., a “posterization candidate” region) determined to be similar (e.g., “closest”) to the attention region).
Since each of Suzuki and Sawada discloses correcting an attention region using a reference region by at least replacing a color of the attention region with a color of the reference region as detailed above, it would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to modify the system of Suzuki to incorporate correcting the attention region using a reference region determined to be similar to the attention region in response to the attention region being determined to be included in the background region to improve the correction of the attention region by maintaining the hue of the original image as taught by Sawada (para(s). [0092]—see citation above).
Where Suzuki in view of Sawada does not specifically disclose
…corrects… the attention region using a reference region determined to have the identical background as the attention region and located closer to the attention region than a reference region determined not to have the identical background as the attention region, from among the reference regions determined to be similar to the attention region
Kanbara teaches in the same field of endeavor of correcting attention regions using reference regions of an identical background to the attention regions
…corrects… the attention region using a reference region determined to have the identical background as the attention region and located closer to the attention region than a reference region determined not to have the identical background as the attention region, from among the reference regions determined to be similar to the attention region (description, para(s). [0110] and [0112-0113], and Fig. 8, recite(s)
[0110] “The correction unit 33b takes a block that includes the image data with which clipped whites or crushed shadows has occurred as being the block for attention, and performs the first correction processing upon that block for attention. Here, although the block for attention is taken as being a region that includes image data with which clipped white or crushed whites has occurred, it is not always necessary for the white portion of the image data to be totally blown or the black portion of the image data to be totally crushed. For example, it would also be acceptable to arrange to take a region where a signal value is greater than or equal to a first threshold value or less than or equal to a second threshold value as being the block for attention. …”
[0112] “… At this time, the area of the reference block is the same as that of the block for attention. …”
[0113] “(i) The correction unit 33b replaces the image data having clipped whites or crushed shadows within the block for attention with the image data that has been acquired for the single reference block that, among the reference blocks that are positioned around the block for attention, is in the position closest to the region where clipped whites or crushed shadows has occurred. Even if a plurality of pixels where clipped whites or crushed shadows has occurred are present within the block for attention, still the image data for this plurality of pixels where clipped whites or crushed shadows has occurred is replaced with the same image data that has been acquired for the above described single reference block in the closest position. For example, on the basis of the image data corresponding to the pixels 86a through 86d included in the reference block 86 that is in the closest position to the pixels where crushed shadows has occurred (i.e. the pixels 85b and 85d) among the reference blocks 81 through 84 and 86 through 89 around the block for attention 85, the image data corresponding to the black crush pixel 85b and the image data corresponding to the black crush pixel 85d are replaced by the same data (for example the image data corresponding to the pixel 86c).”
PNG
media_image1.png
411
467
media_image1.png
Greyscale
, where selecting the “reference block” with the “closest position to the pixels where” a similar background (e.g., a luminance “greater than or equal to”/“less than or equal to” a “threshold value”, such as “crushed shadows” in the example of Fig. 8 above) to a “block for attention” has occurred as replacement for pixels in the “block for attention” is correcting an attention region (e.g., “block for attention”) using a reference region (e.g., “reference block”) determined to have an identical background (e.g., same luminance such as “crushed shadows”) as the attention region and located closer (e.g., “closest [in] position”) to the attention region than a reference region determined not to have the identical background as the attention region (e.g., as depicted in Fig. 8, the selected reference region 86c with an identical background as the attention pixels 85b and 85d of “crushed shadows” is closer than reference region(s) 81a-81d, 84a-84d, and equivalents, which do not have identical backgrounds as the attention region—i.e., not “crushed shadows” backgrounds)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to try using a reference region determined to have an identical background as the attention region and located closer to the attention region than a reference region determined not to have the identical background as the attention region, from among the reference regions determined to be similar to the attention region, because a person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the plurality of reference regions in the system of Suzuki in view of Sawada comprises a plurality of regions having both identical and not identical backgrounds as the attention region (e.g., description, para(s). [0029], of Suzuki disclosed above that “Pixels within a set reference range” include pixels “that are not part of the front-print content” and thus also includes pixels that are “part of the front-print content”) and thus would require the plurality of reference regions to have both identical and not identical backgrounds as the attention region with varying positions from the attention region, such that a reference region determined for use in the correction of the attention region can be a reference region located closer to the attention region than a reference region determined not to have an identical background as the attention region as taught by Kanbara above.
Regarding claim 3, Suzuki, as modified by Sawada and Kanbara, discloses the image processing apparatus according to claim 1, wherein Suzuki further discloses the circuitry is further configured to
determine brightness of the attention region based on the extracted brightness component (description, para(s). [0052-0053], recite(s)
[0052] “…Furthermore, if the characteristics of the scanner are known, foreground pixels can be identified and protected by applying thresholding to the pixel values themselves or the brightness values based on that information. …”
[0053] “If the target is not a foreground pixel, a reference range of a predetermined size is set around the target pixel (step S14), and the pixel values within that reference range are clustered in a specific color space to calculate a representative color (step S15). …”
, where determining if a “target pixel” is a “foreground pixel” or “not a foreground pixel” based on “brightness values” is determining brightness of the attention region based on the extracted brightness component (e.g., “brightness values”)),
wherein the circuitry does not correct the attention region, in response to the brightness of the attention region being determined(description, para(s). [0051]—see citation in claim 1 limitation “classify a plurality of…”—, where “updat[ing] to the next pixel using raster scanning” when the “target pixel is [detected as] a foreground pixel” is not correcting the attention region in response to the brightness of the attention region being determined (i.e., determination of a “foreground pixel” is based on the “brightness value[s]” of the pixel as disclosed previously in para. [0052] above)).
Where Suzuki does not specifically disclose
wherein the circuitry does not correct the attention region, in response to the brightness of the attention region being determined to be lower than a predetermined brightness;
Sawada further teaches in the same field of endeavor of correcting attention regions based on the brightness of the attention region
wherein the circuitry does not correct the attention region, in response to the brightness of the attention region being determined to be lower than a predetermined brightness (para(s). [0048-0051] and [0107], recite(s)
[0048] “…The CPU 21 converts the color value (R, G, B) of the acquired target pixel to the luminance (the Y value) using Expression (1) (step S53). The CPU 21 determines whether the converted Y value is less than a threshold value (th1) (step S55). th1 is a threshold value for determining dark color pixels and is “64,” for example. The dark color is, for example, a color that represents characters and graphics etc. and whose luminance is low (namely, a visually dark color).”
[0049] “When it is determined that the Y value is less than th1 (yes at step S55), the color value of the target pixel is included in a dark color range. In this case, the CPU 21 classifies the target pixel as a second attribute (step S57). …The second attribute is pixel attribute information indicating that the color value of the target pixel corresponds to a dark color.”
[0050] “When it is determined that the Y value is not less than th1 (no at step S55), the CPU 21 calculates a distance L1, which is a distance from the RGB value (backR, backG, backB) of the candidate color for the base color to the color value (R, G, B) of the target pixel (step S59). L1 is a Euclidean distance in the RGB color space. The CPU 21 may calculate L1 using the same technique as Expression (4).”
[0051] “The CPU 21 determines whether the calculated L1 exceeds backth calculated at step S43 (step S61). When it is determined that L1 does not exceed backth (no at step S61), the color value of the target pixel is included in the color range of the background color. In this case, the CPU 21 classifies the target pixel as a first attribute (step S63). …The first attribute is pixel attribute information indicating that the color value of the target pixel corresponds to the background color.”
[0107] “The CPU 21 replaces the color values of the pixels of the first attribute included in the original image data with the candidate color (backY, backCb, backCr) for the base color included in a color value range corresponding to the color of the sheet (step S109). The CPU 21 maintains the color values of the pixels of the second attribute included in the original image data (step S105). In this way, by replacing the background color pixels with the candidate color for the base color, it may be possible to improve the image quality of the original image data. By maintaining the dark color pixels, it may be possible to maintain the hue of the image.”
, where the circuitry “maintain[s] dark color pixels” (i.e., foreground pixels) by not performing processing on not-dark pixels (i.e., pixels with “the [luminance] Y value is not less than [a threshold] th1” and/or “background color [pixels]”) is not performing correction on attention regions determined to be lower than a predetermined brightness (i.e., foreground pixels are regions where “luminance is low” or “the [luminance] Y value is less than [a threshold] th1”)).
Since each of Suzuki and Sawada discloses that attention regions classified as foreground regions based on at least the extracted brightness component of the attention region are not corrected, a person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that the foreground regions disclosed in the system of Suzuki are attention regions determined to be lower in brightness (i.e., “luminance”) as taught by Sawada above.
Regarding claim 4, Suzuki, as modified by Sawada and Kanbara, discloses the image processing apparatus according to claim 1, wherein Suzuki further discloses the circuitry is further configured to
determine a size of regions each having a color similar to the attention region determined as the background, from among the plurality of regions (description, para(s). [0036], recite(s)
[0036] “Figure 1 shows an example of a reference range for correcting bleed-through. If it is determined that back exposure has occurred at the target pixel, the positional relationship (hereinafter referred to as distance D) between that target pixel 2 and the replacement pixel is calculated. In the case of bleed-through of thin lines such as letters or ruled lines, this distance D generally takes a small value. In contrast, in the case of wide back exposure, the distance D increases as you move from the peripheral area to the center, and the maximum distance Dmax (see Figure 1) between a pixel within reference range 1 and the target pixel 2 becomes the upper bound.”
, where determining the “distance” between the “target pixel 2 and the replacement pixel” in the “reference range” is determining a size of regions each having a color similar to the attention region determined as the background (i.e., the “reference range” pixels)),
wherein the circuitry does not correct the attention region, in response to the determined size exceeding the size of the plurality of reference regions (description, para(s). [0036-0037] and [0041], recite(s)
[0036] “…In contrast, in the case of wide back exposure, the distance D increases as you move from the peripheral area to the center, and the maximum distance Dmax (see Figure 1) between a pixel within reference range 1 and the target pixel 2 becomes the upper bound.”
[0037] “If the distance between the target pixel and the replacement pixel exceeds Dmax, the same conditions as described for a single cluster will be met, and no back-image component will be generated at the target pixel.”
[0041] “Here, s is an index representing the size of the back exposure that should be completely corrected, and if the distance D is smaller than s, the target pixel is completely replaced by the replacement pixel. Conversely, if the distance D is greater than the index e, the target pixel is not corrected at all. …”
, where “not correct[ing]” the “target pixel” if the “distance D is greater than the index e” is not correcting the attention region in response to the determined size exceeding (i.e., “greater”) the size of the plurality of reference regions (e.g., “index e”)).
Regarding claim 5, Suzuki, as modified by Sawada and Kanbara, discloses the image processing apparatus according to claim 1, wherein Suzuki further discloses the circuitry is further configured to
calculate a plurality of correction colors used for correcting the attention region using the plurality of reference regions (description, para(s). [0054]—see citation in claim 1 limitation “determine whether…” above—, where the “calculated representative colors” are a plurality of correction colors using the plurality of reference regions (e.g., “reference range”)),
wherein the circuitry combines the calculated plurality of correction colors at a predetermined ratio (description, para(s). [0029], recite(s)
[0029] “First, a reference range of a practical size is set around the target pixel that is subject to back-image detection and correction processing. Since this process uses only pixel information within the set reference range, it is consistent with the online process described above. Pixels within a set reference range that are not part of the front-print content are clustered in a specific color space (e.g., RGB color space), and a representative color is extracted from each cluster. Any clustering method is acceptable as long as it strikes a good balance between speed and accuracy; for example, a linear discriminant function can be used. Similarly, the method for extracting representative colors from each cluster is also the same; the simplest method is to use the average of the pixel values of the pixels belonging to the cluster, or other statistical measures can be used. …”
, where using the “average of the pixel values of the pixels belonging to the cluster” as a correction color (e.g., “representative color”) is combining (i.e., “averaging”) the calculated plurality of correction colors (e.g., each “cluster” of pixels includes a correction color of a “pixel value”) at a predetermined ratio (i.e., “averaging” is combining the “pixel values” of each “cluster” in a ratio of equal parts)) and corrects the attention region using a correction color obtained by the combination (description, para(s). [0053]—see citation in claim 1 limitation “classify a plurality of…”—, where correcting the attention region (e.g., “target pixel”) by “replac[ing]” the color of the “target pixel” using the “representative color” is correcting the attention region using a correction color (e.g., “representative color”) obtained by the combination (e.g., “average of the pixel values belonging to the cluster” as previously recited in para. [0029] above)).
Regarding claim 6, Suzuki, as modified by Sawada and Kanbara, discloses the image processing apparatus according to claim 5, wherein Suzuki further discloses the circuitry is further configured to
calculate a brightest color as a first correction color, from among colors of the plurality of reference regions (description, para(s). [0054]—see citation in claim 1 limitation “determine whether…” above—, where the color of at least one “calculated representative color” is at least a “brightest pixel” is at least a first correction color being at least a first correction color from among the colors of the plurality of reference regions)
calculate a representative color by combining the first correction color(description, para(s). [0029]—see citation in claim 5 limitation “wherein the circuitry combines…” above—, where using the “average of the pixel values of the pixels belonging to the cluster” as a correction color (e.g., “representative color”) is combining (i.e., “averaging”) at least the first correction color (e.g., “brightest pixel”) at a predetermined ratio (i.e., “averaging” is combining the “pixel values” of each “cluster” in a ratio of equal parts)).
Where Suzuki does not disclose
calculate a color darker than the first correction color as a second correction color, using the colors of the plurality of reference regions; and
calculate a representative color by combining the first correction color and the second correction color at a predetermined ratio;
Sawada further teaches in the same field of endeavor of combining a plurality of correction colors
calculate a color darker than the first correction color as a second correction color, using the colors of the plurality of reference regions (para(s). [0056] and [0086] and Fig. 14, recite(s)
[0056] “Based on all the pixels of the acquired target block, the CPU 21 generates a per block average (baveY, baveCb, baveCr), which is an average value of each of the Y values, the Cb values and the Cr values (step S77). …More specifically, the per block average indicates a color value of a representative color that represents the color values of the plurality of pixels included in the target block.”
[0086] “On the other hand, when the target pixel t2 acquired at step S101 is a pixel of the third attribute (yes at step S107), the CPU 21 acquires dY from an area D2 of 3×3 pixels centered on the target pixel t2 (step S121). In the area D2, one pixel adjacent to the right of the target pixel t2 shows a noise image of read minute dirt, for example. Eight pixels of the nine pixels in the area D2, excluding the aforementioned one pixel, show the base color image read from the sheet. In this case, the Y value of the one pixel showing the noise image is a minimum Y value of the area D2. The maximum value of each of the Y values of the eight pixels showing the base color image is a maximum Y value of the area D2. A difference between the minimum Y value and the maximum Y value in the area D2 (i.e., a luminance difference in the area D2) is relatively small. Accordingly, since dY is less than th2 (yes at step S123), the CPU 21 further performs processing described below.”
PNG
media_image2.png
317
349
media_image2.png
Greyscale
, where determining an “average value” of “color values of the plurality of pixels included in the target block” is determining a combination of a plurality of correction colors within reference regions; wherein Fig. 14 depicts that the combination can include a color darker (e.g., the “one pixel adjacent to the right of the target pixel” is a darker pixel of “minimum [luminance] Y value”) than a first correction color of a brightest color among the reference regions (i.e., the “Eight pixels of the nine pixels in the area D2… show the base color image read from the sheet” are brightest pixels of “maximum [luminance] Y value”) as a second correction color (e.g., a “representative color”) using the colors of the plurality of reference regions (i.e., the darker pixel is determined as a “minimum [luminance] Y value” by using the luminance of the other reference regions as a comparison)); and
calculate a representative color by combining the first correction color and the second correction color at a predetermined ratio (para(s). [0056] and [0086] and Fig. 14—see citations immediately above—, where determining an “average value” of “color values of the plurality of pixels included in the target block” is calculating a representative color by combining at least a first correction color (e.g., pixel of “maximum [luminance] Y value”) and a second correction color (e.g., pixel of “minimum [luminance] Y value”) at a predetermined ratio (i.e., “averag[ing]” is combining the correction colors in a ratio of equal parts)).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the presently filed invention to try calculating a color darker than the first correction color as a second correction color using the colors of the plurality of reference regions and calculate a representative color by combining the first correction color and the second correction color at a predetermined ratio because a person of ordinary skill in the art before the effective filing date of the claimed invention would have recognized that each of the plurality of reference regions (e.g., pixel “cluster[s]”) disclosed in Suzuki each have a correction color (e.g., “representative color”) and thus would include correction colors of different brightness (i.e., ‘brighter’ or ‘darker’), including at least a correction color of a brightest color as a first correction color from among colors of the plurality of reference regions and a correction color darker than the first correction color using the colors of the plurality of reference regions, as taught by Sawada above.
Regarding claim 7, Suzuki, as modified by Sawada and Kanbara, discloses the image forming apparatus comprising:
the image processing apparatus according to claim 1 (Suzuki, as modified by Sawada and Kanbara,; see the rejection of claim 1 above); and
circuitry configured to
read an image included in a document and generate the input image, the generated input image being processed by the image processing apparatus to generate the show-through removed image (Suzuki; description, para(s). [0014], recite(s)
[0014] “The invention of claim 1 is a color image processing apparatus that performs image processing to selectively reduce bleed-through on a digital color original image obtained by digitally inputting a color printed original on paper, by detecting and correcting bleed-through, characterized in that it detects the magnitude of the bleed-through as a feature and performs image processing that depends on the magnitude of the bleed-through.”
, where the input “digital color original image” is a generated input image by reading an image included in a document (e.g., “a color printed original on paper”) and the performed “image processing” of correcting “bleed-through” in the generated input image is generating a show-through removed image); and
form the generated input image processed by the image processing apparatus (Suzuki; description, para(s). [0073], recite(s)
[0073] “After the characteristic processing of the present invention described with reference to Figure 9 (step S33), processing such as color correction dependent on the output device is performed, for example, various color processing for printing and various filter processing for display on a display (step S34), and the image is output by an output device such as a printer or display (step S35).”
, where the outputted image is the show-through removed image formed by processing the generated input image by the image processing apparatus).
Regarding claim 8, the claim is the method performed by the apparatus of claim 1. Therefore, claim 8 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 9, the claim differs from claim 1 in that the claim is in the form of a non-transitory computer-readable recording medium storing an image processing program, which when executed by the image processing apparatus of claim 1, causes the image processing apparatus of claim 1 to perform the process of claim 1. Suzuki discloses said non-transitory computer-readable recording medium (description, para(s). [0005], recite(s)
[0005] “The embodiments herein provide a non-transitory computer-readable medium storing computer-readable instructions. The instructions, when executed by a processor of an image processing apparatus, perform processes. …”
). Therefore, claim 9 recites similar limitations to claim 1 and is rejected for similar rationale and reasoning (see the analysis for claim 1 above).
Regarding claim 11, the claim recites similar limitations to claim 3 and is rejected for similar rationale and reasoning (see the analysis for claim 3 above).
Regarding claim 12, the claim recites similar limitations to claim 4 and is rejected for similar rationale and reasoning (see the analysis for claim 4 above).
Regarding claim 13, the claim recites similar limitations to claim 5 and is rejected for similar rationale and reasoning (see the analysis for claim 5 above).
Regarding claim 14, the claim recites similar limitations to claim 16 and is rejected for similar rationale and reasoning (see the analysis for claim 16 above).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JULIA Z YAO whose telephone number is (571)272-2870. The examiner can normally be reached Monday - Friday (8:30AM - 5PM).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Emily Terrell can be reached at (571)270-3717. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/J.Z.Y./Examiner, Art Unit 2666
/MING Y HON/Primary Examiner, Art Unit 2666
Prosecution Insights