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 allowance or after an Office action under Ex Parte Quayle, 25 USPQ 74, 453 O.G. 213 (Comm'r Pat. 1935). 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, prosecution in this application has been reopened pursuant to 37 CFR 1.114. Applicant's submission filed on 4/21/2026 has been entered.
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.
Claim(s) 21-25 is/are rejected under 35 U.S.C. 103 as being unpatentable over Regina et. al. (US 11,334,771 B2)(hereinafter referred to as Regina) in view of Mason er al. (US 2006/0041506)(hereinafter referred to as Mason) and Balakrishnan et al. (US 2021/0124919) (hereinafter referred to as Balakrishnan).
As per claim 21, Regina discloses a method for detecting document fraud, the method comprising (Regina, abstract): receiving an incoming document image associated with an incoming document (Regina, fig. 2 and col. 2, 1st paragraph: inputting an image to the processing such as an image of a electronic document); detecting a plurality of incoming document objects of interest on the incoming document image (Regina, fig. 2 and col. 2, 1st paragraph: a plurality of object detections are obtained in the document image [objects of interest as claimed, by BRI, such as being logo objects); generating one or more incoming document bounding boxes enclosing one or more of the plurality of incoming document objects of interest (Regina, col. 17, 2nd paragraph: bounding box enclosing the object in the document is generated); calculating Intersection over Union (IoU) metrics for the one or more incoming document bounding boxes and one or more reference document bounding boxes enclosing one or more corresponding reference document objects of interest on a reference document (Regina, col. 17, 3rd paragraph: calculation of IoU for the bounding boxes between bounding boxes determining the overlapping hence includes the one or more bounding boxes and one or more reference document bounding boxes as claimed); determining an IoU score based on the IoU metrics (Regina, col. 17, 3rd paragraph: the cluster score is determined based on the IoU determined having IoU value [IoU score]); comparing the incoming document stock image and a reference document stock image (Regina, fig. 2 and col. 6, last 2 paragraphs: comparing the detection with the kept detections [comparing the stock image with a reference document stock image as claimed]); determining an image pattern score based on the comparison of the incoming document stock image and the reference document stock image (Regina, col. 6, last 2 paragraphs: overlapping score is determined according to the result of the comparison [pattern score as claimed being the overlapping score], and the cluster score is determined based on the overlapping score to determine the fraud/phishing); and determining a fraud score based on (1) the IoU score and (2) the image pattern score (Regina, col. 6, last 2 paragraphs, and col. 12, last paragraph: basing on the cluster score, a document can be determined as phishing or not, or invalid and the IoU score and the overlapping score).
Regina does not disclose:
that the incoming document and reference document and associated images are check images and the method is for detecting check fraud;
determining one or more of the plurality of incoming document objects of interest are variable objects of interest in the incoming document image;
creating an incoming document stock image, wherein the incoming document stock image excludes the variable objects of interest;
However in the same art of validating documents, Mason teaches:
that the incoming document and reference document and associated images are check images and the method is for detecting check fraud (Mason, [0078] and [0143]: The documents that are analyzed and compared are checks in order to detect check fraud);
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art for Regina’s document fraud detection to be for check fraud detection, as taught by Mason. The motivation is because check fraud is a well known form of document fraud and there is significant financial benefit it detecting and stopping check fraud (Mason, [0007]).
Additionally, in the same art of document authentication, Balakrishnan teaches:
determining one or more of the plurality of incoming document objects of interest are variable objects of interest in the incoming document image (Balakrishnan, [0011]-[0021]: The invariable attributes, or objects, of the document are determined; thus, the other attributes in the documents are considered variable objects);
creating an incoming document stock image, wherein the incoming document stock image excludes the variable objects of interest (Balakrishnan, [0011]-[0021] and [0068]-[0079]: The document is comparted using only the invariable attributes, thus, excluding the variable objects; the document without the variable objects is considered the stock image);
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art for Regina’s document fraud detection to include comparison based only in invariable attributes, as taught by Balakrishnan. The motivation is to provide more accurate data for comparison to determine document authenticity (Balakrishnan, [0085]-[0087]).
As per claim 22 (dependent on claim 21), Regina in view of Mason and Balakrishnan further teaches:
wherein the plurality of incoming check objects of interest and the one or more corresponding reference check objects of interest are any one of (i) a signature line, (ii) a date line, (iii) a payee line, (iv) a logo, (v) a memo, (vi) a payer information section, (vii) a MICR line, (viii) an amount box, (ix) an amount line, (x) a bank information section, (xi) a check number section, (xii) a routing number section, (xiii) an account number section, (xiv) a bank fractional section, (xv) a security watermark section, (xvi), an endorsement section, or (xvii) any combination of (i)-(xvi) (Mason, fig. 3A and [0048]: Objects of interest for determining check fraud include a variety of check information).
As per claim 23 (dependent on claim 21), Regina in view of Mason and Balakrishnan further teaches:
determining the document is valid based on the fraud score; and approving the document (Regina, col. 12, last paragraph: basing on the cluster score, a document can be determined as phishing or not, or invalid as proving that the document is valid).
As per claim 24 (dependent on claim 23), Regina in view of Mason and Balakrishnan further teaches:
saving the document as a new reference document (Regina, col. 4, 2nd paragraph: discloses the documents can be kept for further filtering of comparing as new reference document).
As per claim 25 (dependent on claim 21), Regina in view of Mason and Balakrishnan further teaches:
determining the document requires review based on the fraud score (Regina, col. 4, 2nd paragraph: discloses combined filtering including score fusion filtering which includes additional filtering [review as claimed, by BRI] including being based on the scores as discussed above including the analogous fraud score); and flagging the document (Regina, col. 3 1st paragraph and col. 4, 2nd paragraph: the result includes flagging the document having phishing or not).
Claims 27-28 are rejected under 35 U.S.C. 103 as being unpatentable over Regina, Mason, and Balakrishnan in view of Murugesan et. al. (“Efficient Privacy-Preserving Similar Document Detection, 2010, The VLDB Journal 19, 457-475”)(hereinafter referred to as Murugesan).
As per claim 27 (dependent on claim 21), Regina, Mason, and Balakrishnan further teaches:
wherein the algorithm is configured such that the algorithm (as discussed above in claim 21).
However, Regina does not explicitly disclose creates hashes in a manner that have close Euclidean distance or cosine similarity between documents from the same document stock and a large Euclidean distance or cosine similarity for documents from different document stocks or altered document stock.
In the same document image processing Murugesan discloses creates hashes in a manner that have close Euclidean distance or cosine similarity between documents from the same document stock and a large Euclidean distance or cosine similarity for documents from different document stocks or altered document stock (Murugesan, section 7, 4th paragraph: discloses cosine similarity is used to find similarity between frequency vectors of the images to determine the similarity between images of documents [any of which is analogous to the current document stock image and the other to be analogous to the reference document stock image], the frequency vector is analogous to creating and storing the has as claimed; the frequency vector is created for both the images; discloses calculating the cosine similarity between the frequency vectors of the images for the processing as discussed).
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to modify Regina, Mason, and Balakrishnan to have an algorithm, the algorithm is configured such that the algorithm creates hashes in a manner that have close Euclidean distance or cosine similarity between documents from the same document stock and a large Euclidean distance or cosine similarity for documents from different document stocks or altered document stock as taught by Murugesan to arrive at the claimed invention discussed above. Such a modification is the result of combing prior art elements according to known methods to yield predictable results. The motivation for the proposed modification would have been to compare images more efficiently (Murugesan, abstract, section 7, 4th paragraph).
As per claim 28 (dependent on claim 27), Regina, Mason, Balakrishnan, and Murugesan further teaches:
wherein comparing the document stock image and the reference document stock image includes (as discussed above in claim 21).
creating and storing a target hash based on the reference document stock image (Murugesan, section 7, 4th paragraph: discloses cosine similarity is used to find similarity between frequency vectors of the images to determine the similarity between images of documents [any of which is analogous to the current document stock image and the other to be analogous to the reference document stock image], the frequency vector is analogous to creating and storing the has as claimed); creating a hash based on the document stock image (the frequency vector is created for both the images); and calculating any one of (i) Euclidean distances between the target hash and the hash, (ii) a cosine similarity between the target hash and the hash, or (iii) a combination of (i) and (ii) (Murugesan, section 7, 4th paragraph: discloses calculating the cosine similarity between the frequency vectors of the images for the processing as discussed).
Allowable Subject Matter
Claims 1-12 and 29-39 are allowed.
Claim 26 is 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
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW W BEE whose telephone number is (571)270-5183. The examiner can normally be reached 9:00 - 7:00 M-Th.
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/ANDREW W BEE/ Supervisory Patent Examiner, Art Unit 2677
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