The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This office action is in response to Applicant’s submission filed on 2 June 2026. THIS ACTION IS NON-FINAL.
In response to the restriction requirement, Applicant’s election with traverse of the instant application in the reply filed on 20 January 2026 is acknowledged.
Status of Claims
Claims 1-20 are pending.
Clams 1-6, 15-20 are withdrawn.
Claim 7 includes limitations interpreted under 35 U.S.C. 112(f), because it uses a generic placeholder coupled with functional language without reciting sufficient structure to achieve the function.
Claims 7-14 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement.
Claims 7-14 are rejected under 35 U.S.C. 112(b) as indefinite.
Claim 7-14 are rejected under 35 U.S.C. 101 for being directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
There is no art rejection for claims 7-14.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
In claim 7, claim limitations “input unit” have been interpreted under 35 U.S.C. 112(f), because they use a generic placeholder coupled with functional language without reciting sufficient structure to achieve the function. Reviewing the specification, it appeared [0025 -0027] described detailed structure of this element, e.g., “… The input unit 110 may include at least one of a key input unit, such as a keyboard or keypad …”. It is construed to be “a keyboard or keypad”.
In claim 7, claim limitations "learning data generation unit", ”learning unit", “determination unit” have been interpreted under 35 U.S.C. 112(f), because they use a generic placeholder coupled with functional language without reciting sufficient structure to achieve the function. The specification does not provide descriptions of the structure of these elements.
If applicant wishes to provide further explanation or dispute the examiner’s interpretation of the corresponding structure, applicant must identify the corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action.
If applicant does not intend to have the claim(s) limitations treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 , sixth paragraph, applicant may amend the claim(s) so that it/they will clearly not invoke 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, or present a sufficient showing that the claim recites/recite sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
For more information, see MPEP § 2173 et seq. and Supplementary Examination Guidelines for Determining Compliance With 35 U.S.C. 112 and for Treatment of Related Issues in Patent Applications, 76 FR 7162, 7167 (Feb. 9, 2011).
Claim Rejections - 35 USC § 112
112(b) Rejection
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.
A claim is indefinite if, when read in light of the specification, it fails to inform, with reasonable certainty, those skilled in the art about the scope of the invention. Nautilus, Inc. v. Biosig Instruments, Inc., 110 USPQ.2d 1688, U.S. Supreme Court (2014).
Claims 7-14 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 pre-AIA the applicant regards as the invention.
Regarding claim 7, including metaphorical terminology lacking structural / procedural definitions: a "learning data generation unit", ”learning unit", “determination unit”, the specification does not provide sufficient structural / procedural description to determine the scope of these limitations, the claims are therefore indefinite.
Regarding claim 7, it never introduce “normal data” as definite noun phrase. It appears only within the determination unit’s function: “determine whether the biometric data is normal data or forged data”. This is a predicate classification (an outcome label), not an antecedent-establishing recitation of a data set. Claim 7 then recites: ”the learning data includes data including a similarity degree with the normal data” – using definite article “the” refer back to a term that was never properly introduced, hence is lack of antecedent basis, the claim is therefor indefinite. For the purpose of clarity and applying prior art, “determine whether the biometric data is normal data or forged data” and “… indicating a similarity degree with the normal data …” is construed to be “determine whether the biometric data is normal or forged” and “…indicating a similarity degree with normal data…”.
Regarding claims 8-14, which depend on above rejected claim 1, are rejected for the same reason.
35 U.S.C. 112(a) Rejections
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 7-14 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
Regarding claim 7, including metaphorical terminology lacking support of structural / procedural description: a "learning data generation unit", ”learning unit", “determination unit”, the specification does not provide sufficient structural / procedural description for these limitations. The claims are therefore rejected for failing to comply with the written description requirement.
Regarding claims 8-14, which depend on above rejected claim 1, are rejected for the same reason.
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.
Judicial Exception
Claims 7-14 of the claimed invention are directed to a judicial exception, an abstract idea, without significantly more.
(Independent Claims) With regards to claim 7,
Step 1: The claim recites a machine, which falls into one of the statutory categories.
Step 2A – Prong 1: the claim, in part, recites:
(a)“…. to generate learning data obtained based on matching first data and second data; … to learn content through the learning data generated by the learning data generation unit ” (mental process and/or math concept), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the language about generic computer elements, “to generate”, “to learn”, in the limitation citied above encompasses creating data for counterfeit detection based on observing / comparing data, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas;
(b) “ to determine whether the biometric data is normal data or forged data based on the content learned in the learning unit…”, (mental process and/or math concept), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the language about generic computer elements, “to determine”, in the limitation citied above encompasses making decision based on observation and comparison, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas;
(c) “…wherein the learning data includes data indicating a similarity degree with the normal data and a matching degree between the first data and the second data” (mental process and/or math concept), as drafted, is a process that, under its broadest reasonable interpretation, covers mathematical concepts but for the recitation of generic computer components. Computing a “similarity degree” and matching degree” between data sets is a mathematical comparison / calculation. Mathematical relationship and algorithms have been found by the courts to be abstract ideas, e.g., see MPEP 2106.04(a)(2) A. Mathematical Relationships, iv. organizing information and manipulating information through mathematical correlations, Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014). The patentee in Digitech claimed methods of generating first and second data by taking existing information, manipulating the data using mathematical functions, and organizing this information into a new form. The court explained that such claims were directed to an abstract idea because they described a process of organizing information through mathematical correlations, like Flook's method of calculating using a mathematical formula. 758 F.3d at 1350, 111 USPQ2d at 1721. If a claim limitation, under its broadest reasonable interpretation, covers mathematical relationships, then it falls within the “Mathematical Concepts” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Step 2A – Prong 2: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of: (a) “a learning data generation unit”, “a learning unit”, “an input unit”, “a determination unit”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… to receive biometric data”, which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)); The claim is directed to an abstract idea.
Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites the additional elements of: (a) “a learning data generation unit”, “a learning unit”, “an input unit”, “a determination unit”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… to receive biometric data””, which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)), which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)). The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory"). Accordingly, the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible.
(Dependent claims)
Claims 8-14 are dependent on claim 7 and include all the limitations of claim 7. Therefore, claims 8-14 recite the same abstract ideas.
With regards to claim 8, the claim recites further limitation of “… wherein the first data comprises data in which biometric information and non- physical information including a same part as the normal data are mixed, andthe second data comprises data in which biometric information different from the normal data and body information are mixed” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 9, the claim recites further limitation of “… wherein the non- physical information comprises material information indicating materials providing the biometric information of the first data, wherein the materials providing the biometric information of the first data are different from materials providing the biometric information of the normal data” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 10, the claim recites further limitation of “…to select, from the data in which biometric information different from the normal data and body information are mixed, a particular data that is determined to be similar to the normal data, and determine the selected data as the second data” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 11, the claim recites further limitation of “… to determine the matching degree between the first data and the second data, and generate data having a matching degree equal to or greater than a threshold value as the learning data” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 12, the claim recites further limitation of “… wherein the determination of the matching degree determines the matching degree in a matching plane of the first data and the second data” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 13, the claim recites further limitation of “… to search for a variable in which the matching degree between the first data and the second data is maximized as a variable having a maximum matching degree, and re-determine the matching degree between the first data and the second data to which the variable having the maximum matching degree is applied, to generate the data having the matching degree equal to or greater than the threshold value as the learning data” (mental process and/or math concept), which is further process of observing / analyzing / processing data for counterfeit detection, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
With regards to claim 14, the claim recites further limitation of “… wherein the variable having the maximum matching degree comprises at least one of a matching angle, a matching position, brightness of the first data or the second data, or humidity of the first data or the second data” (mental process and/or math concept), which is math concept. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible.
Allowable Subject Matter
Claims 7-14 include allowable subject matter since when reading the claims in light of the specification, as per, MPEP §2111.01 or Toro Co. v. White Consolidated Industries Inc., 199F.3d 1295, 1301, 53 USPQ2d 1065, 1069, 1069 (Fed.Cir. 1999), none of the references of record alone or in combination disclose or suggest the combination of limitations specified in claims 7-14.
In interpreting the claims, in light of the specification filed on 2 June 2026, the Examiner finds the claimed invention to be patentably distinct from the prior arts of record.
Regarding the amended independent claims, the primary reason for the allowance is the inclusion of the specific process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
None of the cited prior art references, singly or in combination, fully teaches all limitations of independent claim 7.
Regarding the dependent claims, which include all the limitations of the independent claims, are also allowed.
The followings are references close to the invention claimed:
Fujimaki et al., US-PGPUB NO.20100131800A1 [hereafter Fujimaki] teaches fault detection using ML models. However Li does not teach the specific claimed process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
Ochiai et al., US-PGPUB NO.20190166039A1 [hereafter Fujimaki] teaches data matching using similarity degree. However Ochiai does not teach the specific claimed process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
Boshra et al., US-PATENT NO.8275178B2 [hereafter Boshra] teaches finger print counterfeit detection. However Boshra does not teach the specific claimed process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
Nogueira et al., “Fingerprint liveness detection using convolutional neural networks”, IEEE Trans. On information forensics and security, Vol.11, No.6, Jun 2016 [hereafter Nogueira] teaches fingerprint liveness detection using CNNs. However Nogueira does not teach the specific claimed process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
Ghiani et al., “LivDet 2013 Fingerprint liveness detection competition 2013”, ICB 2013 [hereafter Ghiani] teaches generating artificial fingerprint data for counterfeit detection. However Ghiani does not teach the specific claimed process / structure of synthesizing adversarial training data by matching two complementary, incomplete data sources, pre-filtered by similarity to registered data, then fused and scored by both similarity and matching degree values embedded in the resulting learning data.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TSU-CHANG LEE whose telephone number is 571-272-3567. The fax number is 571-273-3567.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas, can be reached 571-272-2589.
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/TSU-CHANG LEE/
Primary Examiner, Art Unit 2128
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