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 .
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.
Claims 1–20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
In January, 2019 (updated October 2019), the USPTO released new examination guidelines setting forth a two-step inquiry for determining whether a claim is directed to non-statutory subject matter. According to the guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g., an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the claims are directed toward non-statutory subject matter, as shown below:
STEP 1: Do the claims fall within one of the statutory categories? Yes. All claims fall within a statutory category under § 101.
Claim 1: method.
Claims 19 and 20: non-transitory computer-readable storage device/software program product) and Device.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon or an abstract idea? Yes, the claims are directed to an abstract idea.
With regard to STEP 2A (PRONG 1), the guidelines provide three groupings of subject matter that are considered abstract ideas:
Mathematical concepts – mathematical relationships, mathematical formulas or equations, mathematical calculations;
Certain methods of organizing human activity – fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions); and
Mental processes – concepts that are practicably performed in the human mind (including an observation, evaluation, judgment, opinion).
Claim 1 is directed to the abstract idea of Mathematical Concepts and Mental Processes.
Specifically, the claim recites "obtaining a first masked image... a second masked image... and obtaining a degree of overlap." The "degree of overlap" is a mathematical calculation (specifically, Intersection over Union or IoU). Mathematical formulas and the calculation of ratios between data sets are well-recognized as abstract ideas (see Gottschalk v. Benson).
Furthermore, the logic of determining whether a "biometric image block" is contained within a "medium image block" is a mental process that can be performed by a human through simple observation. A human looking at a photograph of a person holding a mobile phone can mentally identify the boundary of the phone (the medium) and the boundary of the face (the biometric) and determine if the face is "within" the phone screen. Performing this observation on a computer using digital masks does not change the nature of the underlying mental/logical process.
To distinguish ineligible claims that merely recite a judicial exception from eligible claims that require an implementation of judicial exception, the Supreme Court uses a two-step framework: Step One (Step 2A), determine whether the claims at issue are directed to one of those patent-ineligible concepts; and Step Two (Step 2B), if so, ask “what else is there in the claims?’ to determine whether the additional elements transform the nature of the claim into a patent eligible application.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? No, the claim does not recite additional elements that integrate the judicial exception into a practical application.
With regard to STEP 2A (prong 2), whether the claim recites additional elements that integrate the judicial exception into a practical application, the guidelines provide the following exemplary considerations that are indicative that an additional element (or combination of elements) may have integrated the judicial exception into a practical application:
an additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
While the guidelines further state that the exemplary considerations are not an exhaustive list and that there may be other examples of integrating the exception into a practical application, the guidelines also list examples in which a judicial exception has not been integrated into a practical application:
an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea;
an additional element adds insignificant extra-solution activity to the judicial exception; and
an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.
The claims do not integrate the abstract idea into a "practical application" that provides a technical improvement to the computer's functionality.
The claim describes a series of functional steps: (a) receiving an image, (b) segmenting the image, (c) generating masks, and (d) performing a mathematical comparison. These steps represent the mere collection of data, followed by the application of a mathematical algorithm to that data, and finally the output of a result ("liveness detection result"). The Federal Circuit has held that "collecting data, analyzing it, and displaying the results" is not a practical application that confers eligibility (see Electric Power Group, LLC v. Alstom S.A.).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? No, the claim does not recite additional elements that amount to significantly more than the judicial exception.
With regard to STEP 2B, whether the claims recite additional elements that provide significantly more than the recited judicial exception, the guidelines specify that the pre-guideline procedure is still in effect. Specifically, that examiners should continue to consider whether an additional element or combination of elements:
adds a specific limitation or combination of limitations that are not well-understood, routine, conventional activity in the field, which is indicative that an inventive concept may be present; or
simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, which is indicative that an inventive concept may not be present.
The following computer functions have been recognized as well‐understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality): receiving or transmitting data over a network. See MPEP 2106.05(d)(II).
There is no indication that the claim elements, individually or in combination, perform any function beyond the ordinary use of a computer executing an algorithm. The claims do not provide any unconventional architecture, sensor arrangement, or computer operation that would transform the abstract idea into a patent-eligible application.
Accordingly, the claims do not recite any additional elements sufficient to amount to “significantly more” than the abstract idea itself. See Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018); SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161 (Fed. Cir. 2018).
The claims do not recite an "inventive concept" sufficient to transform the abstract idea into a patent-eligible invention. Each of the elements recited, when considered individually or as an ordered combination, is "well-understood, routine, and conventional" in the field of computer vision.
Semantic Segmentation: Using neural networks (such as the Encoder-Decoder architecture in Claim 8) for segmentation was a standard technique in the art prior to the effective filing date.
Mask Generation: Generating binary masks for object detection is a core function of conventional architectures like Mask R-CNN, as evidenced by Zhu et al. (2021), which describes generating masks for "spoofing mediums" and "persons" to detect contours.
IoU Calculation: The use of Intersection over Union (IoU) to determine spatial relationships between detection blocks is a fundamental building block of object detection systems.
The combination of these elements simply implements the abstract idea of "comparing two areas to see if they overlap" using conventional computer vision tools. The claims do not improve the computer's ability to segment images or process data; rather, they merely use the computer as a tool to execute a logical process for a specific application (face liveness).
Thus, since claims 1, 19, and 20 are: (a) directed toward an abstract idea, (b) does not recite additional elements that integrate the judicial exception into a practical application, and (c) does not recite additional elements that amount to significantly more than the judicial exception, it is clear that claims 1,19, and 20 are directed towards non-statutory subject matter.
Further, dependent claims 2–18 further limit the abstract idea without integrating the abstract idea into practical application or adding significantly more. Each of the claimed limitations either expand upon or add either 1) new mathematical process, 2) a new additional element, 3) previously presented mathematical process, and/or 4) a previously presented additional element.
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) 1-7, 17-20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (Detection of Spoofing Medium Contours for Face Anti-Spoofing, from IDS) in view of Halet (20210117709).
Regarding claim 1, Zhu discloses an image liveness detection method, comprising (abstract):
performing semantic segmentation processing on a to-be-detected image to obtain a first masked image corresponding to a medium image block in the to-be-detected image (abstract, section II-B Object detection, mask R-CNN and section III, generating an object mask)
obtaining, through calculation, a degree of overlap between the medium image block and the biometric image block based on the first masked image and the second masked image (section IV-A, CEM-RCNN, intersection over union); and
determining a liveness detection result of the to-be-detected image according to the degree of overlap (section IV-A, spoof image determining).
Halet teaches performing a biometric recognition on the to-be-detected image to obtain boundary information of a biometric image block in the to-be-detected image (see par. 69 of Halet);
processing pixels of the to-be-detected image based on the boundary information to obtain a second masked image corresponding to the biometric image block (par. 69 of Halet, coordinates of the face zone).
It would have been obvious prior to the effective filing date of the invention to one of ordinary skill in the art to include in Zhu the ability to set a biometric determination region as taught by Halet in order to set a biometric bounding area to calculate the liveliness.
Regarding claim 2, Zhu teaches determining an intersection image block and a union image block between the medium image block and the biometric image block; calculating a first image block area of the intersection image block, and calculating a second image block area of the union image block; and calculating a ratio of the first image block area to the second image block area as the degree of overlap (see section IV-A and IV-B and V-A and V-B, IoU calculation).
Regarding claim 3, Zhu teaches determining an intersection image block and a union image block between the medium image block and the biometric image block; calculating a number of intersection pixels in the intersection image block, and calculating a number of union pixels in the union image block; and calculating a ratio of the number of intersection pixels to the number of union pixels as the degree of overlap (see section IV-A and IV-B and V-A and V-B, IoU calculation).
Regarding claim 4, Zhu teaches in response that the degree of overlap is greater than or equal to a preset degree-of-overlap threshold, determining the to-be-detected image as a spoofing image; and in response that the degree of overlap is less than the preset degree-of-overlap threshold, determining the to-be-detected image as a live image (see section IV-A and IV-B and V-A and V-B, IoU calculation).
Regarding claim 5, Zhu teaches in response that the degree of overlap is greater than or equal to a preset degree-of-overlap threshold, calculating an area of the medium image block and an area of the biometric image block; in response that the area of the biometric image block is greater than or equal to the area of the medium image block, determining the to-be-detected image as a live image; and in response that the area of the biometric image block is less than the area of the medium image block, determining the to-be-detected image as a spoofing image (see section IV-A and IV-B and V-A and V-B, IoU calculation. Also see section V-F, ratio between the facial area and the whole captured image).
Regarding claim 6, Zhu and Halet teach inputting the to-be-detected image into a biometric recognition module for performing the biometric recognition to obtain the biometric image block; and constructing the boundary information according to position information of a boundary pixel of the biometric image block in the to-be-detected image (see Halet par. 69, coordinate boundary locations and section V-B of Zhou, mask contours).
Regarding claim 7, Zhu and Halet teach determining a target image block in the to-be-detected image based on the boundary information, wherein the to-be-detected image comprises the target image block and the biometric image block; binarizing pixels in the biometric image block in terms of their pixel values and pixels in the target image block in terms of their pixel values to obtain the second masked image; and wherein the pixels in the biometric image block that are binarized in terms of their pixel values are determined to be of a first pixel value, and the pixels in the target image block that are binarized in terms of their pixel values are determined to be of a second pixel value (par. 69 of Halet and Zhu teach mask prediction in section II-B and section III).
Regarding claim 17, see the abstract and section I of Zhu and par. 69 of Halet.
Regarding claim 18, see section 1 of Zhu and par. 69 of Halet.
Regarding claims 19-20, see the rejection of claim 1.
Allowable Subject Matter
Claims 8-16 are 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.
Also the 101 rejection must be overcome.
Claim 8 recites in part: inputting the to-be-detected image into a semantic segmentation model, wherein the semantic segmentation model comprises a first encoder and a first decoder; and wherein the first encoder performs feature extraction on a spoofing medium in the to-be-detected image to obtain a medium feature corresponding to the spoofing medium, and the first decoder performs semantic segmentation on the to-be-detected image based on the medium feature to obtain the first masked image.
Claim 9 recites in part: inputting the to-be-detected image into a semantic segmentation model, wherein the semantic segmentation model comprises a second encoder, a second decoder and an image processing module; and wherein the second encoder is configured to perform layer-wise feature extraction and down-sampling on a spoofing medium in the to-be-detected image to obtain semantic features of respective layers; the second decoder is configured to fuse the semantic features of the respective layers and perform up-sampling, to obtain an up-sampled image having a same size as the to-be-detected image; the image processing module is configured to perform discretization processing on the up-sampled image to obtain a grayscale image, and perform binarization processing on the grayscale image to obtain the first masked image.
Regarding claim 15, judging, based on the boundary information, whether the biometric image block conforms to a preset feature rule; in a case that the biometric image block conforms to the preset feature rule, processing the pixels of the to-be-detected image based on the boundary information to obtain the second masked image corresponding to the biometric image block; wherein the preset feature rule comprises at least one of: being greater than a reflectance threshold, there being an artifact, there being a Moiré pattern, and there being a specular reflection.
Claim 16 recites in part, in a case that boundary information of a plurality of biometric image blocks is detected, calculating an area of each of the biometric image blocks according to the boundary information; and determining a biometric image block having a largest area, and removing all biometric image blocks except for the biometric image block having the largest area.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HADI AKHAVANNIK whose telephone number is (571)272-8622. The examiner can normally be reached 9 AM - 5 PM Monday to Friday.
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/HADI AKHAVANNIK/Primary Examiner, Art Unit 2676