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 Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 5, 7, 8, 12, 14, 15, 18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over USPN 9,674,498 to Mukherjee et al. (“Mukherjee”) (cited on the IDS filed 1/27/25) in view of US 2012/0062699 to Diggins.
Regarding claim 1, Mukherjee discloses a method comprising:
obtaining, using at least one processing device of an electronic device (Fig. 12, element 1202; column 16, line 53 – column 17, line 40), an image (Fig. 6, elements 600, 610; column 9, lines 17-53, wherein a set of images is obtained, each frame of which is then processed individually);
dividing, using the at least one processing device, the image vertically into a first vertical half and a second vertical half (Fig. 6, element 620; Fig. 7, element 710; column 10, lines 9-32, wherein the histogram cue module divides each selected image/frame left and right halves (i.e. first and second vertical halves));
determining, using the at least one processing device, a first histogram score representing a resemblance between histograms of the first vertical half and the second vertical half (Fig. 6, element 620; Fig. 7, element 720; column 10, lines 9-64, wherein a binned color histogram is determined for the left and right halves and a histogram distance (i.e. first histogram score) representing resemblance/similarity between the two is computed);
dividing, using the at least one processing device, the image horizontally into a first horizontal half and a second horizontal half (Fig. 6, element 620; Fig. 7, element 710; column 10, lines 9-32, wherein the histogram cue module divides each selected image/frame top and bottom halves (i.e. first and second horizontal halves));
determining, using the at least one processing device, a second histogram score representing a resemblance between histograms of the first horizontal half and the second horizontal half (Fig. 6, element 620; Fig. 7, element 720; column 10, lines 9-64, wherein a binned color histogram is determined for the top and bottom halves and a histogram distance (i.e. first histogram score) representing resemblance/similarity between the two is computed); and
identifying, using the at least one processing device, whether the image is a left-right (LR) stereo image type, a top-bottom (TB) stereo image type, or a mono image type using the Fig. 6, element 620; Figs. 7, elements 730-780; column 10, line 65 – column 12, line 20, wherein the histogram scores are used to determine if the image, and the set of images, is a left/right stereo image type, top/bottom stereo image type, or a 2D/mono image type).
However, as noted by the double-strikethroughs above, Mukherjee does not disclose expressly determining, using the at least one processing device, a first similarity score representing a similarity between the first vertical half and the second vertical half, wherein the first similarity score is based on pixel differences between the first vertical half and the second vertical half; determining, using the at least one processing device, a second similarity score representing a similarity between the first horizontal half and the second horizontal half, wherein the second similarity score is based on pixel differences between the first horizontal half and the second horizontal half; and then identifying, using the at least one processing device, whether the image is a left-right (LR) stereo image type, a top-bottom (TB) stereo image type, or a mono image type using the first similarity score, the second similarity score.
Diggins discloses a method comprising:
dividing an image vertically into a first vertical half and a second vertical half (Fig. 1; paragraphs 19 and 33-39, wherein the image is divided into first and second vertical halves);
determining a first similarity score representing a similarity between the first vertical half and the second vertical half, wherein the first similarity score is based on pixel differences between the first vertical half and the second vertical half (paragraphs 19 and 33-39, wherein a cross-correlation measure (i.e. first similarity score) is evaluated for side by side halves (i.e. first and second vertical halves);
dividing the image horizontally into a first horizontal half and a second horizontal half (Fig. 1; paragraphs 19 and 33-39, wherein the image is divided into first and second horizontal halves);
determining a second similarity score representing a similarity between the first horizontal half and the second horizontal half, wherein the second similarity score is based on pixel differences between the first horizontal half and the second horizontal half (paragraphs 19 and 33-39, wherein a cross-correlation measure (i.e. second similarity score) is evaluated for over and under halves (i.e. first and second horizontal halves); and
identifying whether the image is a left-right (LR) stereo image type, a top-bottom (TB) stereo image type, or a mono image type using the first similarity score and the second similarity score (paragraph 37, wherein the image is determined to be a side-by-side (i.e. LR) stereo image, over/under stereo image, or not stereoscopic (i.e. mono image) based on the cross-correlation measures (i.e. similarity scores)).
Mukherjee & Diggins are combinable because they are from the same art of image processing, specifically identifying if an image is a LR stereo, TP stereo, or mono image.
It would have been obvious to a person of ordinary skill in the art, before the effective filing date of the claimed invention to incorporate the technique of identifying if an image is a LR stereo, TP stereo, or mono image based on vertical and horizontal image half similarity scores, as taught by Diggins, with the process of identifying if an image is a LR stereo, TP stereo, or mono image based on vertical and horizontal image half histogram scores disclosed by Mukherjee.
The suggestion/motivation for doing so would have been a more robust determination of whether an image is stereoscopic by adding the benefit of detecting stereoscopic images based on the similarities between image halves and without undue cost (Diggins, paragraphs 01-06).
Therefore, it would have been obvious to combine Diggins with Mukherjee to obtain the invention as specified in claim 1.
Regarding claim 5, the combination of Mukherjee and Diggins discloses the method of Claim 1, wherein identifying whether the image is the LR stereo image type, the TB stereo image type, or the mono image type includes:
determining a first prediction, based on a score threshold and using the first similarity score and the first histogram score, of whether the image is the LR stereo image type (Mukherjee, Fig. 7, elements 750, 760 and 770; column 11, line 31 – column 12, line 6, wherein the first histogram score is compared with a LR threshold to predict and identify if the image/frame is of a LR stereo type. Diggins, paragraph 37, wherein the first similarity score is compared with a high/low threshold to predict and identify if the image is of the LR stereo image type);
determining a second prediction, based on the score threshold and using the second similarity score and the second histogram score, of whether the image is the TB stereo image type (Mukherjee, Fig. 7, elements 750, 760 and 770; column 11, line 31 – column 12, line 6, wherein the second histogram score is compared with a TB threshold to predict and identify if the image/frame is of a TB stereo type. Diggins, paragraph 37, wherein the first similarity score is compared with a high/low threshold to predict and identify if the image is of the TB stereo image type);
identifying, if the first prediction indicates the image is the LR stereo image type, the image as the LR stereo image type (Mukherjee, Fig. 7, elements 750, 760 and 770; column 11, line 31 – column 12, line 6, wherein the first histogram score is compared with a LR threshold to predict and identify if the image/frame is of a LR stereo type. Diggins, paragraph 37, wherein the first similarity score is compared with a high/low threshold to predict and identify if the image is of the LR stereo image type);
identifying, if the second prediction indicates the image is the TB stereo image type, the image as the TB stereo image type (Mukherjee, Fig. 7, elements 750, 760 and 770; column 11, line 31 – column 12, line 6, wherein the second histogram score is compared with a TB threshold to predict and identify if the image/frame is of a TB stereo type. Diggins, paragraph 37, wherein the first similarity score is compared with a high/low threshold to predict and identify if the image is of the TB stereo image type); and
identifying, if the first prediction and the second prediction indicate the image is neither the LR stereo image type nor the TB stereo image type, the image as the mono image type (Mukherjee, Fig. 7, elements 750, 760 and 770; column 11, line 31 – column 12, line 6, wherein the second histogram score is compared with a mono threshold to predict and identify if the image/frame is of a mono image type. Diggins, paragraph 37, wherein the first similarity score is compared with a high/low threshold to predict and identify if the image is neither a LR or TB stereo image type, thereby indicating it as a mono image type).
Regarding claim 7, the combination of Mukherjee and Diggins discloses the method of Claim1, wherein the histograms of the first vertical half and the second vertical half and the histograms of the first horizontal half and the second horizontal half each represent pixel value frequencies in the one of the first vertical half, the second vertical half, the first horizontal half, and the second horizontal half of the image (Mukherjee, Fig. 8 and column 10, lines 33-50).
Regarding claim 8, please refer to the limitations of claim 1 above. Mukherjee further discloses an electronic device comprising at least one processing device configured to carry out the process (Fig. 12, element 1202; column 16, line 53 – column 17, line 40).
Claims 12 and 14 recite similar limitations to those of claims 5 and 7, and are therefore rejected for the same reasoning indicated above with regards to claims 5 and 7.
Regarding claim 15, please refer to the limitations of claim 1 above. Mukherjee further discloses a non-transitory readable medium comprising instructions that when executed cause at least one processor of an electronic device to carry out the process (Fig. 12, elements 1222, 1228; column 17, lines 48-59).
Claims 18 and 20 recite similar limitations to those of claims 5 and 7, and are therefore rejected for the same reasoning indicated above with regards to claims 5 and 7.
Claims 6, 13 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over USPN 9,674,498 to Mukherjee et al. (“Mukherjee”) in view of US 2012/0062699 to Diggins in view of US 2019/0246887 to Oh.
Regarding claim 6, the combination of Mukherjee and Diggins discloses the method of claim 1.
However, the combination of Mukherjee and Diggins does not disclose expressly normalizing the first vertical half and the second vertical half for exposure and/or brightness prior to determining the first similarity score and normalizing the first horizontal half and the second horizontal half for exposure and/or brightness prior to determining the second similarity score.
Oh discloses a process of matching stereo images that includes first normalizing the brightness of them to improve texture (paragraph 87).
Mukherjee, Diggins & Oh are combinable because they are from the same art of image processing, specifically with regards to stereo 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 incorporate the technique of normalizing the brightness of stereo images, as taught by Oh, into the process of identifying if an image is a LR stereo, TP stereo, or mono image disclosed by the combination of Mukherjee and Diggins.
The suggestion/motivation for doing so would have been to improve texture for the process of matching stereo images (Oh, paragraph 87).
Therefore, it would have been obvious to combine Oh with Mukherjee and Diggins to obtain the invention as specified in claim 6.
Claims 13 and 19 recite similar limitations to those of claim 6, and are therefore rejected for the same reasoning indicated above with regards to claim 6.
Allowable Subject Matter
Claims 2-4, 9-11, 16 and 17 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON W CARTER whose telephone number is (571)272-7445. The examiner can normally be reached 8am - 5pm (Mon - Fri).
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, John Villecco can be reached at (571) 272-7319. 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.
/AARON W CARTER/Primary Examiner, Art Unit 2661
Prosecution Insights