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 .
Specification
The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed.
The following title is suggested: Anomaly Detection Based on Restoration Loss Between Input Image and Restoration Image Using Restoration Neural Network
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.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: the preprocessing unit, restoration unit and determination unit of claims 1-4 which each utilize the nonce term unit, functionally define the invention and are not terms recognized by those of ordinary skill to denote structure. Corresponding structure and algorithms have been identified in the instant specification.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 102
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 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.
Claims 1-3, 5-7 and 9 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Ye {Ye, Fei, et al. "Attribute restoration framework for anomaly detection." IEEE Transactions on Multimedia 24 (2020): 116-127}.
Claim 1
In regards to claim 1, Ye discloses an anomaly detection apparatus comprising:
a preprocessing unit configured to generate a context image obtained by removing detailed information from an input image
{See IIIA, figs. 1, 2 copied below including Attribute Erasing Module (AEM) that erases/removed detailed information from an input image. See also IVA in which attribute erasing may include graying which erases color and averages pixel values to remove detailed information. It is also noted that this step is disclosed by the instant specification as being an optional step as per Figs. 3 and 6.};
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a restoration unit configured to approximate the context image to the input image through an artificial neural network so as to convert the context image into a restoration image
{See IIIB, fig. 2, Attribute Restoration Network (ARNet). See also abstract and Introduction}; and
a determination unit configured to determine whether the input image is abnormal based on a loss between the input image and the restoration image converted from
the context image
{See IIIC, figs. 1, 2 Anomaly Measurement based on loss/restoration error. See also Table 1}.
Claims 2 and 3
Ye discloses (claim 2) a training unit configured to train the artificial neural network by restoring detailed information removed from a normal training image and (claim 3) wherein the training unit is configured to update a parameter of the artificial neural network so that a loss between the training image and a restoration image obtained by approximating a context image from which the detailed information is removed from the training image to the training image falls within a configuration value
{initially, it is noted that these claims refer to the normal/conventional training of a restoration network such that the loss converges
{See Abstract, Introduction, Section IIIA, IIIB including training dataset contains normal data and anomalous data is not used for training and training with normal training images to update parameters of the ARNet so that the loss function l2 converges. See also Section IIID and IV in which the training process is performed until convergence (loss within a configuration value)}.
Claims 5-7 and 9
The rejection of apparatus claims 1-3 and 1 above applies mutatis mutandis to the corresponding limitations of method claims 5-7 and computer readable medium claim 9 while noting that the rejection above cites to both device and method disclosures. For the computer readable storage medium storing program limitations of claim 9 see section IV including implementations using a GPU, memory, etc. for the ARNet clearly indicating a computer-implemented embodiment that may use a computer readable medium storing software for execution.
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.
Claims 4 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Ye and Matsumoto (WO-2021161823-A1). A marked-up machine translation of Matsumoto has been provided with this office action, all cross-references are with respect to this translation and the mark-ups are hereby incorporated by reference to further demonstrate claim mapping.
Claims 4 and 8
In regards to claims 4 and 8, Ye discloses wherein the determination unit is configured to determine that the input image is abnormal when the loss between the input image and the restoration image converted from the context image is
Matsumoto is a highly relevant and analogous reference that teaches all of the elements of claim 1 except for the disclosed-as-optional preprocessing step. See abstract, pgs. 2-5 including applying a restoration model 20 trained with normal data to determine an anomaly in the input image data on the basis of the restoration error.
Matsumoto also teaches wherein the determination unit is configured to determine that the input image is abnormal when the loss between the input image and the restoration image converted from the context image is equal to or greater than a threshold value {see pgs. 2-6, 10, fig. 5, Step S13, comparison unit 32 that determines presence/absence of an anomaly by comparing the restoration error L with a threshold value T.
It 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 to have modified Ye which already discloses a determination unit that is configured to determine that the input image is abnormal based on the loss between the input image and the restoration image converted from the context image such that this determination is when the loss between the input image and the restoration image is equal to or greater than a threshold value as taught by Matsumoto because Matsumoto motivates using a threshold on pg. 10, fig. 11 which is to detect abnormalities without omission using a properly chosen threshold, because there is a reasonable expectation of success and/or because doing so merely combines prior art elements according to known methods to yield predictable results.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
L. Zhu, Q. Zhang and W. Wang, "Residual Attention Dual Autoencoder for Anomaly Detection and Localization in Cigarette Packaging," 2020 Chinese Automation Congress (CAC), Shanghai, China, 2020, pp. 475-480, doi: 10.1109/CAC51589.2020.9327200 discloses anomaly detection and localization using a residual attention autoencoder, attention map generator and reconstruction neural network. See fig. 3 copied below and related disclosure
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Yang, Jie, et al. "Visual anomaly detection for images: A survey." arXiv preprint arXiv:2109.13157 (2021) surveys a variety of anomaly detection prior art that employs image reconstruction to detect defects based on the reconstruction error. See section IIIC.
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/MICHAEL ROBERT CAMMARATA/Primary Examiner, Art Unit 2667