DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This is in response to the applicant response filed on 09/12/2025. In the applicant’s response, claims 1, 3-5, and 7-9 were amended; claims 2, and 6 were cancelled. Accordingly, claims 1, 3-5, and 7-9 are pending and being examined. Claims 1, 8, and 9 are independent form.
Claim Rejections - 35 USC § 103
3. 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.
4. 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 of this title, 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.
5. Claims 1, and 4-5, and 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Wolf et al (US 2011/0206246, hereinafter “Wolf”) in view of Hagiwara et al et al (US 2019/0303653, 2014, hereinafter “Hagiwara”).
Regarding claim 1, Wolf discloses an information processing apparatus (see abstract: “A method and system for statistical mapping between genetic information [i.e., the genotype] and facial image data [i.e., the phenotype] including collecting a multiplicity of sets of genetic information and matching facial image data representing a multiplicity of individuals.” See para.256: “a particular feature of the present invention that correlations between genotype and phenotype can be identified even in the absence of a direct causal relationship therebetween.”) comprising: a memory storing instructions; and one or more processors (these hardware related features are inherent in the method/system of Wolf) configured to execute the instructions to
detect genetic information from a biological sample of a person of interest (see 200 of fig.2 and para.303: “using genetic information includes statistical mapping functionality which collects a multiplicity of sets of genetic information 200”; wherein “the genetic information of each of the multiplicity of individuals is expressed or represented as a first multidimensional representation, such as a [the 1st genotype] vector”, see para.304.);
extract a phenotype from an expression portion where a phenotype representing a genetic trait appears based on the genetic information (ibid.);
extract feature points from a biological image and to determine a phenotype by analyzing a shape along the feature points (see 202 of fig.2 and para.303: “matching facial image data 202 representing a multiplicity of individuals”; wherein “the facial image data of each of the multiplicity of individuals is expressed or represented as a second multidimensional representation, such as a [the 2nd phenotype] vector”, see para.304); and
see 87% match degree facial image 220 of fig.2 and para.353: “During the deployment stage, queries can be sent to the system. Each query consists of a genetic signature of one person and several possible matching images and the system returns a matching score for each image. The higher the score, the more likely the image matches the given DNA signature.” It should be noticed that “the matching” is “the DNA-to-image match”, namely, the match between the 1st genotype vector detected from DNA 210 to the 2nd phenotype vector extracted from the each of the facial images 218. See para.352: “The DNA collected from the crime scene is matched against the face or other images of suspects captured by surveillance cameras nearby the crime scene, .... The DNA-to-image match of the best score, or the several matches of the highest scores suggest possible suspects.”).
As explained above, the mere difference is that, Wolf does not disclose “the extracted genetic information” represented in a phenotypic site of an individual includes “dominant” and “recessive” phenotypes as recited in the claim. However, this is common knowledge for one of ordinary skill in the art. As evidence, in the same field of endeavor, Hagiwara teaches: “[a] phenotypic site” refers to a site representing various traits in appearance due to inheritance. “Genetic phenotype or phenotype” refers to a trait, type, physical character represented in the phenotypic site. For example, the genetic phenotype represented in a phenotypic site “front hairline” includes a dominant trait (so-called widow's peak) and a recessive trait (non-widow's peak).” See paragraph [0048]. It therefore would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made to incorporate the teachings of Hagiwara into the teachings of Wolf and utilize the recessive phenotype included in the genotype vector to reduce the number of facial images to be matched. Suggestion or motivation for doing so would have been to extract phenotypic sites representing genetic phenotypes of a living entity from an image and generate genetic information of the living entity captured in the image based on the phenotypic sites as extracted for person identification as taught by Hagiwara, see para.19-21. Therefore, the claim is unpatentable over Wolf in view of Hagiwara.
Regarding claim 4, the combination of Wolf and Hagiwara discloses the information processing apparatus according to claim2, wherein the processor is configured to output a facial image, which degree of matching with respect to the biological sample is greater than a predetermined threshold among a plurality of facial images, as a candidate of a facial images corresponding to the biological sample (Wolf, see the matching facial 220 of fig.2 and para.317: “provides an output 220 indicating which of the candidate persons has the greatest likelihood of being the individual whose genetic information 210 is supplied to mapper 212 and thus selects the facial image of the individual from among the facial images of the plurality of candidate persons.”).
Regarding claim 5, the combination of Wolf and Hagiwara discloses the information processing apparatus according to claim 2, wherein the processor is configured to extract the phenotype by referring to a predetermined position corresponding to the expression portion in the genetic information (Wolf, see para.354: “the system receives genetic signatures and face images of the same persons, i.e., the system receives pairs (M.sub.i, P.sub.i), i=1 . . . N, where M.sub.i is a set of genetic markers for person i (genetic signature), and P.sub.i is facial image of the same person.”).
Regarding claim 7, the combination of Wolf and Hagiwara discloses the information processing apparatus according to claim 2, further comprising a database configured to store, for each of a plurality of facial images, a value of the phenotype detected from the facial image at each expression portion in association with identification information of the facial image (Wolf, see the correspondence between genotypes 202 and facial images 200 in fig.2; see para.303: “the image recognition using genetic information includes statistical mapping functionality which collects a multiplicity of sets of genetic information 200 and matching facial image data 202 representing a multiplicity of individuals.” See para.354: “the system receives genetic signatures and face images of the same persons, i.e., the system receives pairs (M.sub.i, P.sub.i), i=1 . . . N, where M.sub.i is a set of genetic markers for person i (genetic signature), and P.sub.i is facial image of the same person.”).
Regarding claims 8, and 9, each of which is an inherent variation of claim 1, thus it is interpreted and rejected for the reasons set forth in the rejection of claim 1.
6. Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Wolf in view of Claes et al (“Modeling 3D facial shape from DNA”, 2014, hereinafter “Claes”). Claes is cited by applicant in IDS filed on 04/26/2022.
Regarding claim 3, the combination of Wolf and Hagiwara does not explicitly disclose, “the processor stores weights determined beforehand for respective expression portions in the memory, and a degree of matching is calculated for each expression portion by using a value indicating the phenotype extracted from the biological sample, a value indicating the phenotype determined from the facial image, and the weights, and the degree of matching between the biological sample and the facial image is calculated by aggregating degrees of matching for all expression portions” as recited in the claim. However, in the same field of endeavor, Claes, see page.6, the right col., and the last paragraph, clearly discloses “[t]he normal-range results of the SNP in rsl074265 in SLC35Dl (Figure 6A) indicate strong effects at the eyes and periorbital regions, including notable differences at the supraorbital region, as well as at the midface and the chin.” Page.8, the right col., Claes discloses “[t]he normal-range results of the SNP rsl3267109 in FGFRJ depicted in Figure 6B indicate the strongest effects in the supraorbital ridges, the eyes, the midface, the nose, and the comers of the mouth. The strongest differences in the shape transformations are indeed the forehead, supraorbital ridges and nasal bridge.” It therefore would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention was made to incorporate the teachings of Claes into the teachings of the combination of Wolf and Hagiwara and use different weights for different facial portions of a facial image to determine the weighted matching degree in all the different portions between the genotype vector detected from the DNA sample and the phenotype vector extracted from the facial image in the method taught by Wolf. Suggestion or motivation for doing so would have been to consider the properties that SNP (single-nucleotide polymorphism) effects (or, SNP genotypes) are different in different facial portions as taught above by Claes. Therefore, the claim is unpatentable.
Response to Arguments
7. Applicant's arguments with respect to claim 09/12/2025 have been considered but are moot in view of the new ground(s) of rejection. Specifically, in the same field of endeavor, Hagiwara teaches the argued features. Therefore, examiner maintains rejections.
Conclusion
8. 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 extension fee 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 date of this final action.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to RUIPING LI whose telephone number is (571)270-3376. The examiner can normally be reached 8:30am--5:30pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, HENOK SHIFERAW can be reached on (571)272-4637. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RUIPING LI/Primary Examiner, Ph.D., Art Unit 2676