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 .
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.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
35 U.S.C. 101 requires that a claimed invention must fall within one of the four eligible categories of invention (i.e. process, machine, manufacture, or composition of matter) and must not be directed to subject matter encompassing a judicially recognized exception as interpreted by the courts. MPEP 2106. The four eligible categories of invention include: (1) process which is an act, or a series of acts or steps, (2) machine which is an concrete thing, consisting of parts, or of certain devices and combination of devices, (3) manufacture which is an article produced from raw or prepared materials by giving to these materials new forms, qualities, properties, or combinations, whether by hand labor or by machinery, and (4) composition of matter which is all compositions of two or more substances and all composite articles, whether they be the results of chemical union, or of mechanical mixture, or whether they be gases, fluids, powders or solids. MPEP 2106(I).
Claim 10 is rejected under 35 U.S.C. 101 as not falling within one of the four statutory categories of invention because the broadest reasonable interpretation of the instant claims in light of the specification encompasses transitory signals (Specification pg. 13: “The storage 150 may include a nonvolatile memory, such as a ROM, an erasable programmable ROM (EPROM), an electrically EPROM (EEPROM), and a flash memory, a hard disk, a removable disk, or any well-known computer-readable recording medium in the art to which the present invention pertains”; Specification pg. 28-29: “The term ‘manufactured article’ includes a computer program, carrier, or media accessible from any computer-readable device. For example, the computer-readable medium includes, but is not limited to, magnetic storage devices (e.g., hard disk, floppy disk, magnetic strip, etc.), optical disks (e.g., compact disc (CD), digital versatile disc (DVD), etc.), smart cards, and flash memory devices (e.g., EEPROM, card, stick, key drive, etc.). In addition, various storage media presented herein include one or more devices and/or other machine-readable media for storing information. The term ‘machine-readable medium’ includes, but is not limited to, wireless channels and various other media capable of storing, retaining, and/or transmitting instructions(s) and/or data” emphasis added).
Transitory signals are not within one of the four statutory categories (i.e. non-statutory subject matter). See MPEP 2106(I). Claims directed toward a non-transitory computer readable medium may qualify as a manufacture and make the claim patent-eligible subject matter. MPEP 2106(I). Therefore, amending the claims to recite a “non-transitory computer-readable medium” would resolve this issue.
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 1-10 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.
Claims 1 and 10 recite the limitation “determining an identity between the reference product and the comparison target product based on the similarity score.” The limitation renders the claims indefinite because it is not clear how a product forms an identity with another product. For the purpose of further examination, the claims have been interpreted as determining an identity of a product based on a comparison between the reference and target images.
Claims 2-9 depend from claim 1 and therefore inherit all of the deficiencies of claim 1 discussed above.
Claim 7 further recites the limitation “appropriate illuminance value.” The term “appropriate” is a relative and/or subjective term which renders the claim indefinite. The term is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is not clear what is considered to be appropriate vs. inappropriate because illuminance value changes depending on the objects, camera/display settings, weather, etc.
A claim that requires the exercise of subjective judgment without restriction renders the claim indefinite. In re Musgrave, 431 F.2d 882, 893, 167 USPQ 280, 289 (CCPA 1970). Claim scope cannot depend solely on the unrestrained, subjective opinion of a particular individual purported to be practicing the invention. Datamize LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350, 75 USPQ2d 1801, 1807 (Fed. Cir. 2005)); see also Interval Licensing LLC v. AOL, Inc., 766 F.3d 1364, 1373, 112 USPQ2d 1188 (Fed. Cir. 2014).
For the purpose of further examination, the claim has been interpreted as comparing a captured illuminance value to a reference illuminance value.
Claim 8 further recites “specific image,” “specific product,” and “specific digital certificate.” .” The term “specific” is a relative and/or subjective term which renders the claim indefinite. The term is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. It is not clear what is considered to be specific vs. non-specific, and further unclear how these images, products, and digital certificates differ from first and second images, reference and target products, and a previously-recited digital certificate.
A claim that requires the exercise of subjective judgment without restriction renders the claim indefinite. In re Musgrave, 431 F.2d 882, 893, 167 USPQ 280, 289 (CCPA 1970). Claim scope cannot depend solely on the unrestrained, subjective opinion of a particular individual purported to be practicing the invention. Datamize LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350, 75 USPQ2d 1801, 1807 (Fed. Cir. 2005)); see also Interval Licensing LLC v. AOL, Inc., 766 F.3d 1364, 1373, 112 USPQ2d 1188 (Fed. Cir. 2014).
For the purpose of further examination, the term “specific” has been interpreted as “predetermined” or “known.”
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 6, 9, and 10 is/are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Jaber et al. (US 2015/0169638 A1), hereinafter referred to as Jaber.
Regarding claim 1, Jaber teaches a method of identity determination based on artificial intelligence, which is performed by a computing device including at least one processor (Jaber ¶¶0017: “one or more real-world objects to be identified via image recognition”; Jaber ¶¶0071: “the metric fusion can be performed according via learning functions”), comprising:
acquiring a first image of a reference product (Jaber ¶¶0017: “The query image can be an image taken by a user using a digital camera, mobile phone camera, tablet camera, etc., and can contain one or more real-world objects to be identified via image recognition”; Jaber Fig. 4: query image 400);
acquiring a second image of a comparison target product which is a comparison target of the reference product (Jaber ¶¶0017: “The verification engine can be configured to receive a set of candidate images from the candidate database, corresponding to the results of an image recognition process executed on a query image”; Jaber ¶¶0018: “Based on one or more of the candidate images in the results set, the verification engine can select a verification technique to use in verifying the candidates”; Jaber ¶¶0093: “the similarity between the candidate images can be determined by comparing the match scores of each candidate with the query image, or by performing matching between the images in the returned candidate set”; Jaber Fig. 4: candidate image 410 or 420);
acquiring a plurality of first features corresponding to the first image and a plurality of second features corresponding to the second image by inputting the first image and the second image to a feature extraction model (Jaber ¶¶0089: “the query image ROI can be generated based on feature-based matching (such as via SIFT) of the candidate image ROI to the query image”; Jaber Fig. 4: 401 is matched with 411, 402-403 are matched with 421-422; also see Jaber ¶¶0104: “At step 502, an image recognition system implements a feature-based algorithm (in this example, SIFT) and returns a plurality of candidate images from a candidate image database, such as candidate database 102”; Jaber ¶¶0110: “At step 508, the verification engine 101 ranks, classifies or otherwise sorts the candidate images based on the generated scores. In an alternative, the ranking can be performed based on a fusion metric. In this example, the fusion metric can be generated by the engine 101 based on the NCC score and one or more common features between the query image and the returned candidate images”; Jaber Fig. 5);
generating a plurality of feature pairs by matching the plurality of first features and the plurality of second features (Jaber Fig.4 & ¶¶0089 discussed above; further see Jaber ¶¶0066: “For each image verification technique, a confusion matrix can be generated for a given reference image set such that a degree of similarity (e.g., a likelihood or degree of confusion) is calculated for every pairing of images within the reference image set”; Jaber ¶¶0072: “image processing and matching techniques can be paired or otherwise mapped together (such as according to features or characteristics of the image processing and matching techniques) whereby the selection of one of the image processing and matching techniques results in the selection of a corresponding other of the matching or image processing technique”);
acquiring a similarity score for each of the plurality of feature pairs by inputting two features constituting each of the plurality of feature pairs to a similarity analysis model (Jaber ¶¶0093 & ¶¶0110 discussed above; also see Jaber ¶¶0128: “The verification engine 101 can determine a consistency in match scores between the query image and one or more non-query images, against the same candidate images for verification. This consistency score can be a similarity of match scores (e.g., within a certain range or percentage of one another), and can be used at least in part to classify, re-rank or otherwise confirm the recognition performed on the query image”); and
determining an identity between the reference product and the comparison target product based on the similarity score (Jaber Fig. 1: 111-112; Jaber ¶¶0129: “the verification engine 101 can employ feature tracking across a sequence of query images to verify an initial recognition”; Jaber Fig. 5: 507-508).
Regarding claim 2, Jaber teaches the method of claim 1, wherein the generating of the plurality of feature pairs by matching the plurality of first features and the plurality of second features includes generating n*m feature pairs by matching each of n first features corresponding to the first image with each of m second features corresponding to the second image (Jaber Figs. 4-5 & ¶¶0072, ¶¶0089, ¶¶0093, ¶¶0128 discussed above; Jaber ¶¶0054: “Examples of matching techniques include a correlation algorithm, a normalized cross-correlation (‘NCC’) algorithm, a mutual information algorithm, an FFT algorithm, a histogram matching algorithm, and a Hausdorff distance algorithm”; Jaber ¶¶0096: “The type of image signature that is generated can depend on the verification technique to be used. For example, a color down-sampled version of the images can be used when using an NCC technique (e.g., 32 x 32 pixels or other desired size), a down-sampled version of the images can be used for rigid and non-rigid registration identifiers (e.g. 32 x 32 pixels, or other desired size), quantized color histogram pins (e.g., a vector of 16 or 32 numbers) can be used as the signature for a color-histogram-distance technique, and an edge or corner map (such as a binary map) can be used for the Hausdorff-distance technique”).
Regarding claim 6, Jaber teaches the method of claim 1, wherein the feature extraction model is a model pre-trained to extract a plurality of features from an image when the image is input (Jaber ¶¶0143: “The training executed by verification engine 101 can also include the building and updating of candidate database 102. The database building can include the addition of new candidate images as well as a modification to existing images”), and
the similarity analysis model is a model pre-trained to allow the feature extraction model to output a similarity score between features extracted from each of two different images (Jaber Figs. 1, 5, & ¶¶0093, ¶¶0110, ¶¶0128, ¶¶0143 discussed above).
Regarding claim 9, Jaber teaches an apparatus comprising:
a memory configured to store one or more instructions (Jaber ¶¶0038: “verification engine 101 can be embodied as a computer-executable instructions stored on one or more non-transitory computer readable storage media that, when executed by one or more computer processors, cause the one or more computer processors to carry out functions of the inventive subject matter associated with the verification engine 101”); and
a processor configured to execute the one or more instructions stored in the memory (Jaber ¶¶0038 discussed above; Jaber ¶¶0049: “the system 100 can, in addition to the components, functions and processes illustrated in FIG. 1, include some or all of the components and functions (e.g., processors, computer-executable instructions stored in non-transitory memory, dedicated hardware devices, etc.) associated with the initial image recognition”),
wherein the processor executes the one or more instructions to perform the method of claim 1 (Jaber ¶¶0038 & ¶¶0049 discussed above).
Regarding claim 10, Jabber teaches a computer-readable recording medium on which a program for executing a method of providing a surgery simulation in conjunction with a computing device is recorded (Note that when reading the preamble in the context of the entire claim, the recitation “providing a surgery simulation” is not limiting because the body of the claim describes a complete invention and the language recited solely in the preamble does not provide any distinct definition of any of the claimed invention’s limitations. Thus, the preamble of the claim(s) is not considered a limitation and is of no significance to claim construction. See Pitney Bowes, Inc. v. Hewlett-Packard Co., 182 F.3d 1298, 1305, 51 USPQ2d 1161, 1165 (Fed. Cir. 1999). See MPEP § 2111.02 Jaber ¶¶0038 & ¶¶0049 discussed above; Jaber ¶¶0046: “the query image 103 can be an image captured by a …medical imaging system … and provided to an image recognition system”), wherein the method comprises:
acquiring a first image of a reference product (Jaber ¶¶0017 & Fig. 4 discussed above);
acquiring a second image of a comparison target product which is a comparison target of the reference product (Jaber ¶¶0017, ¶¶0018, ¶¶0093 & Fig. 4 discussed above);
acquiring a plurality of first features corresponding to the first image and a plurality of second features corresponding to the second image by inputting the first image and the second image to a feature extraction model (Jaber ¶¶0089, ¶¶0104, ¶¶0110 & Figs. 4-5 discussed above);
generating a plurality of feature pairs by matching the plurality of first features and the plurality of second features (Jaber ¶¶0066, ¶¶0072, ¶¶0089 & Fig. 4 discussed above);
acquiring a similarity score for each of the plurality of feature pairs by inputting two features constituting each of the plurality of feature pairs to a similarity analysis model (Jaber ¶¶0093, ¶¶0110, ¶¶0128 discussed above); and
determining an identity between the reference product and the comparison target product based on the similarity score (Jaber ¶¶0129 & Figs. 1, 5 discussed above).
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.
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.
Claim(s) 3-5 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jaber et al. (US 2015/0169638 A1), in view of Suk et al. (US 2012/0148164 A1), hereinafter referred to as Jaber and Suk, respectively.
Regarding claim 3, Jaber teaches the method of claim 1, further comprising selecting a verification technique to determine the most similar candidate based on the similarity score when the similarity score for each of the plurality of feature pairs is acquired (Jaber ¶¶0075: “A classification of the images can include the verification engine 101 executing one or more of a confirmation of an initial ranking, a re-ranking of the candidate images, a reordering of the candidate images, and a removal of one or more candidate images from consideration”; Jaber ¶¶0078: “To mitigate the risk of false-positive match confirmations, the verification engine 101 can, in embodiments of the inventive subject matter, compare the generated match scores to a threshold necessary for confirmation. The threshold can be an absolute match score that must be met by the highest-ranking candidate such that the candidate can be confirmed as a match, can be a minimum match score ‘improvement’ from the initial image recognition confidence score to the post-verification process match score, a difference in post-verification match score between a highest-scoring candidate and the next highest-scoring candidate, or other suitable thresholds. If the highest-scoring candidate (and, optionally, one or more of the other candidates) does not meet the threshold, the verification engine 101 can resubmit the candidate set for further processing”; Jaber ¶¶0117: “the query image having the candidate image with highest confidence score among all of the candidate images for all query images can be the ‘winner’, and the verification technique selected for that query image can be applied to all other query images”),
wherein the determining of the identity between the reference product and the comparison target product includes determining the identity based on the similarity score for the main feature pairs (Jaber Figs. 1, 5, & ¶¶0129 discussed above).
However, Jaber does not appear to explicitly teach selecting a plurality of main feature pairs from among the plurality of feature pairs.
Pertaining to the same field of endeavor, Suk teaches selecting a plurality of main feature pairs from among the plurality of feature pairs (Suk Fig. 2; Suk ¶¶0030: “The feature point matcher 1220 receives information regarding feature points from the feature point extractor 1210. The feature point matcher 1220 selects a feature point most similar to the feature point of the reference image from among the feature points of the target image, and determines the selected feature point of the reference image and the selected feature point of the target image as a matching pair”; Suk ¶¶0037: “When performing a matching operation for a feature point P among the feature points of the reference image, the feature point matcher 1220 measures similarity between the feature point P and the M feature points of the target image, and matches the feature point P with a feature point of the target image most similar to the feature point P. Such matching operation is performed for each of the N feature points of the reference image”; Suk ¶¶0041: “The feature point matcher 2220 sets a matching candidate region by using a homography matrix (or a homography matrix in manufacturing a product) that has been generated in a previous stage, and thus decreases the number of similarity operations compared to the feature point matcher 1220 of FIG. 1”).
Jaber and Suk are considered to be analogous art because they are directed to image processing. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the image recognition verification technique (as taught by Jaber) to select a subset of features (as taught by Suk) because the combination can prune the features to obtain the most accurate/similar result (Suk ¶¶0031).
Regarding claim 4, Jaber, in view of Suk, teaches the method of claim 3, wherein the selecting of the plurality of main feature pairs from among the plurality of feature pairs based on the similarity scores when the similarity score for each of the plurality of feature pairs is acquired includes:
recognizing overlapping feature pairs composed of mutually overlapping features among the plurality of features (Jaber Fig. 4 discussed above; Jaber ¶¶0087: “The ROIs of candidate images can overlap (i.e., multiple candidate images can have the same or similar ROIs), or be unique to a candidate image relative to one or more other candidate images”; Suk Fig. 4: matching candidate region); and
selecting a specific feature pair with a highest similarity score from among the overlapping feature pairs as the main feature pair (Jaber ¶¶0078 & ¶¶0117 discussed above; Jaber ¶¶0069: “the verification engine 101 can select the confusion matrix based on the candidate image selected as the closest match in initial recognition (i.e., based on the product, family, class, category, etc. of the closest match). In embodiments, the confusion matrix can be selected based on two or more candidate images from the candidate set 104 determined to be most similar among the candidate set (e.g., identified belonging to a same family, class, category, etc.)”; Jaber ¶¶0076: “The classified candidate images 105 now show candidate image C having the highest match score, followed by images B, A, and D”).
Regarding claim 5, Jaber, in view of Suk, teaches the method of claim 3, wherein the determining of the identity based on the similarity score for the main feature pair includes:
recognizing the number of feature pairs with a similarity score exceeding a preset size among the main feature pairs (Jaber ¶¶0078 & ¶¶0117 discussed above; Jaber ¶¶0069: “more than one confusion matrix corresponding to more than one grouping (e.g. more than one product family or other organized grouping) can be selected, such as if the candidate images 104 correspond to products from different (but similar-looking) product families or if there are two equal (or nearly equal within a desired percentage of similarity) top candidates within the image set 104”; Jaber ¶¶0118: “The uniform verification technique can be selected based on the query image having the greatest number of common candidate images, the number of query images having the common candidate images, etc. The techniques described for the other examples can be used as tie-breakers if more than one query image fits the selection criteria of this example”); and
recognizing that the reference product and the comparison target product are the same when the number of the feature pairs exceeds the preset number (Jaber ¶¶0069: “the verification engine 101 can select the confusion matrix based on the candidate image selected as the closest match in initial recognition (i.e., based on the product, family, class, category, etc. of the closest match)”).
Allowable Subject Matter
Claims 7-8 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 7, the prior art of record teaches that it was known at the time the application was filed to acquire an image of a reference product or a second image of a comparison target product (Jaber ¶¶0017, ¶¶0018, ¶¶0093 & Fig. 4 discussed above).
The prior art further teaches that it was known to perform the actions according to a user query or return request of a user (Jaber ¶¶0047: “the user context information can be in the form of a query … or a stated purpose … The query image 103 can comprise still image data or video image data”; Ramos Fig. 2).
However, the prior art, alone or in combination, does not appear to explicitly teach providing a capturing guide including at least one of a first capturing guide that displays a reference image around a capturing screen, a second capturing guide that displays the reference image by overlapping the reference image on the capturing screen, and a third capturing guide that compares an illuminance value recognized through the capturing screen with a reference illuminance value and displays the compared illuminance value on the capturing screen.
Regarding claim 8, the prior art of record teaches that it was known at the time the application was filed to use the method of claim 1, further comprising verifying the product using image recognition (Jaber Abstract).
However, the prior art, alone or in combination, does not appear to explicitly teach authenticating a connection relationship between a product and a digital certificate, wherein the authenticating of the connection relationship between the product and the digital certificate includes:
acquiring an image captured from a product and a digital certificate corresponding to the product;
acquiring a plurality of third features corresponding to the digital certificate;
acquiring a plurality of fourth features by inputting the image into the feature extraction model;
generating a plurality of feature pairs for authentication by matching the plurality of third features and the plurality of fourth features;
acquiring a similarity score for each of the plurality of feature pairs for authentication by inputting two features constituting each of the plurality of feature pairs for authentication to a similarity analysis model; and
determining whether the specific product is a product corresponding to the digital certificate based on the similarity scores.
Note that the examiner’s statement of reasons for indicating allowable subject matter applies to the claims only as interpreted by the examiner due to indefinite claim language. The statement may no longer apply if amendments change the scope of the claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SOO J SHIN whose telephone number is (571)272-9753. The examiner can normally be reached M-F; 10-6.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571)272-7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Soo Shin/Primary Examiner, Art Unit 2667 571-272-9753
soo.shin@uspto.gov
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