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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/28/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-2, 5-7 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation “the classifier module”, "the quantum-trained classifier module" and “the image.” There is insufficient antecedent basis for this limitation in the claim. The same goes for claims 6 and 8.
Although claim 1 is amended based on filed Fig. 2, the claim languages are confusing. For example, “a classifier module”, “the classifier module”, “a quantum-trained classifier module” and “the quantum-trained classifier module” seem to be interchangeable freely throughout the claim. It is indefinite to interpret whether all four limitations refer to 1) the same module, 2) the same module at different stages/times, 3) different modules, or 4) different modules at different stages/times. If the terms are different entities, using descriptive “first’ and “second” would be advised. Otherwise, “the…” (e.g., the classifier module) would be advised to follow through after “a…” (e.g., a classifier module) is disclosed.
Moreover, there is lack of clarification in amended claim to separate images of training images (215 of Fig. 2) and new image (225 of Fig. 2). Similarly, “image pre-processing module” (230 of Fig. 2) would need clarification from “image pre-processing module” (220 of Fig. 2). It’d be indefinite to interpret “the trained quantum vision system” processing images (training image or new image?) from “the image pre-processing module.” If they are the same module, limitation would be needed to clarify the same module at different stages/times.
For examination purpose, amended claims cannot be properly considered until indefiniteness are corrected.
Response to Arguments
Applicant's arguments filed 11/28/2025 have been fully considered but they are not persuasive.
Regarding amended claims 1, 6 and 8, applicant argued that prior arts failed to teach amended claims.
However, as explained in response to 112(b) rejections above, due to indefiniteness of language in amended claims. The amended claims cannot be properly considered until indefiniteness are corrected.
Thus, rejections are properly maintained.
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.
Claim(s) 1-2, 5-9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US2024/0127458) in view of Chellapilla et al. (US2004/0181749) and Ramesh et al. (US2022/0292675).
To claim 1, Zhang teach a computer-implemented method of classifying an image comprising:
enhancing contrast of the image (paragraph 0039, contrast enhancement);
applying dimension reduction to the contrast-enhanced image (paragraph 0039, down sampled);
passing the contrast-enhanced and dimensionally reduced image to a trained machine learning vision system; and generating a first result classified by the trained machine learning vision system (paragraph 0039, then input to a ML model (e.g., a deep learning model, convolutional neural networks (CNNs) (e.g., basic CNN, R-CNN, inception model, residual neural network, etc.) and detectors that are built on convolutional neural network (e.g., Single Shot MultiBox Detector (SDD), You Only Look Once (YOLO), etc.) to detect and classify a person).
But, Zhang do not expressly disclose the machine learning vision system being quantum-trained; splitting the contrast-enhanced and dimensionally reduced image into at least two areas depending on the first result; passing the at least two areas of the contrast-enhanced and dimensionally reduced image to the quantum-trained classifier module and generating a second result classified by the quantum-trained classifier module.
Chellapilla teach passing an input image to a trained classifier and generating a first result classified by the trained classifier; splitting the input image into at least two areas depending on the first result; passing the at least two areas to the trained classifier and generating a second result classified by the trained classifier (Fig. 3; paragraphs 0061-0062), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the method of Zhang, in order to implement refined classification.
Ramesh teach training an image classifier by one or more classical and quantum computing devices located in one or more locations (paragraph 0040).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate teaching of Ramesh and modify the method of Zhang and Chellapilla into using quantum computing devices for training, in order to provide alternative classifier training implementation by design preference.
To claim 6, Zhang, Chellapilla and Ramesh teach a computer-implemented method of training a classifier module to classify a plurality of images (as explained in response to claim 1 above).
To claim 8, Zhang, Chellapilla and Ramesh teach a system for the classification of images (as explained in response to claim 1 above).
To claims 2 and 9, Zhang, Chellapilla and Ramesh teach claims 1 and 8.
Zhang, Chellapilla and Ramesh teach wherein the enhancing of the image comprises one of contrast stretching or histogram equalization (Zhang, paragraph 0039).
To claims 5 and 7, Zhang, Chellapilla and Ramesh teach claims 1 and 6.
Despite of lack of disclosure in Zhang, Chellapilla and Ramesh, the number of dimensions after applying the dimension reduction being at least ten dimensions is well-known in the art to be a design preference, which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Zhang, Chellapilla and Ramesh by design preference, hence Official Notice is taken.
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhang et al. (US2024/0127458) in view of Chellapilla et al. (US2004/0181749), Ramesh et al. (US2022/0292675), and Wang (WO2021042509).
To claim 10, Zhang, Chellapilla and Ramesh teach claim 8.
But, Zhang, Chellapilla and Ramesh do not expressly disclose wherein the image pre-processing module is adapted to reduce the number of dimensions of the image using principal component analysis.
Wang teach image preprocessing operation include reducing image dimension through a principal component analysis method (page 5, third paragraph), which would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate into the method of Zhang, Chellapilla and Ramesh by design preference.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ZHIYU LU whose telephone number is (571)272-2837. The examiner can normally be reached Weekdays: 8:30AM - 5:00PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Stephen R Koziol can be reached at (408) 918-7630. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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ZHIYU . LU
Primary Examiner
Art Unit 2669
/ZHIYU LU/Primary Examiner, Art Unit 2665 June 16, 2026
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