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 .
Claim Interpretation – 112(f)
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:
“obtaining unit, configured to…”; and “processing unit, configure to…” in claim 11; and
“output unit…configured to…” in claim 13.
The corresponding structure for performing the function of the “obtaining unit”, “processing unit” and “output unit” is a processor executing a program stored in memory (i.e. computer), see figures 4, 5 and paragraph 131, as well as the entire corresponding algorithm for performing the functions associated with the units, as is detailed throughout the specification and drawings, and summarized by the combination of claims 11-18. See also “Computer-Implemented Means-Plus-Function Limitations” MPEP 2181(II)(B).
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
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.
Claims 1-5, 7, 19 and 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 2020/0294222 to Wen et al. (“Wen”).
Regarding claim 1, Wen discloses a method for defect detection (Fig. 2), comprising:
obtaining a defect eigenvector of an image to be detected (paragraphs 46-48, wherein features are extracted from the subimage and used to obtain a target/defect eigenvector);
calculating a similarity score of the image to be detected for each known defect type according to the defect eigenvector (paragraphs 37, 46-48, wherein, using a deep CNN defect classification model, the target/defect eigenvector is compared to each eigenvector of known defects in the table to determine a known eigenvector that are identical or similar, corresponding to calculating a similarity score); and
performing defect classification on the image to be detected according to the similarity score (paragraph 49-50, wherein at least one defect category for the subimage is obtained based on the calculated similarities, corresponding to performing defect classification on the image).
Regarding claim 2, Wen discloses the method according to claim 1, wherein the calculating a similarity score of the image to be detected for each known defect type according to the defect eigenvector comprises:
mapping the defect eigenvector into a trained eigenvector space, wherein the trained eigenvector space comprises a distribution position of a defect eigenvector of the known defect type (paragraphs 37, 46-48, wherein mapping/comparing the target/defect eigenvector to known defect eigenvectors in the table/space is done by a trained Deep CNN classification model (Fig. 4)); and
calculating a distance between the defect eigenvector and the defect eigenvector of the known defect type, so as to obtain the similarity score of the image to be detected for each known defect type (paragraphs 37, 46-48, wherein, as is known in the art, the trained Deep CNN calculates a distance/difference between the target/defect eigenvector and each of the known defect eigenvectors so as to obtain a similarity score used to identify the most appropriate defect category).
Regarding claim 3, Wen discloses the method according to claim 2, wherein the performing defect classification on the image to be detected according to the similarity scores comprises:
when a maximum similarity score in similarity scores is not less than a similarity threshold, outputting a defect type corresponding to the maximum similarity score (paragraph 48, wherein if the compared eigenvectors are identical or similar (i.e. not less than a similarity threshold) then the corresponding defect type is output);
OR
when the similarity scores are all less than the similarity threshold, outputting an unknown defect type (alternative limitation).
Regarding claim 4, Wen discloses the method according to claim 3, further comprising:
outputting the similarity score corresponding to the defect type (paragraphs 37 and 48, wherein as is known in the art, a deep CNN provides outputs a correlation/similarity score associated with the categories/patterns it is trained to recognize).
Regarding claim 5, Wen disclose the method according claim 1, wherein the obtaining a defect eigenvector of an image to be detected comprises:
obtaining the defect eigenvector by an encoding module (paragraphs 37 and 48, wherein the deep CNN corresponds to an “encoding module” configured to create/obtain the target/defect eigenvector from extracted features).
Regarding claim 7, Wen discloses he method according to claim 5, further comprising:
obtaining defect position information of the image to be detected by a decoding module (paragraphs 37 and 48, wherein the deep CNN corresponds to an “decoding module” configured to “decode” an image to obtain the position of defects).
Regarding claim 19, Wen discloses an apparatus for defect detection, comprising a processor and a memory, wherein the memory is configured to store a program, and the processor is configured to call the program from the memory and run the program to perform the method for defect detection according to claim 1 (Figs. 6 and paragraphs 86-90).
Regarding claim 20, Wen discloses a non-transitory computer-readable storage medium, storing a computer program, wherein the computer program, when run on a computer, causes the computer to perform the method for defect detection according to claim 1 (Figs. 6 and paragraphs 86-90).
Allowable Subject Matter
Claims 11-18 allowed.
Claims 6 and 8-10 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.
The following is an examiner’s statement of reasons for allowance:
Regarding independent claim 11, as explained above, the limitations “obtaining unit, configured to…” and “processing unit, configured to…” invoke 112(f), which are considered to be computer-implemented means-plus-function limitations, and therefore the structure for performing the associated functions of those units is a processor/computer executing a program stored in memory (i.e. computer), see figures 4, 5 and paragraph 131, as well as the entire corresponding algorithm as is detailed throughout the specification and drawings, and summarized by the combination of claims 11-18. As discussed above with regards to independent claim 1, the prior art of Wen (US 2020/0294222) discloses a similar process of comparing a target eigenvector with eigenvectors of known defects to determine a defect classification. However, neither Wen nor any other prior art found teach or fairly suggests the details of the “encoding module” portion of the algorithm used to obtain the defect eigenvector or “decoding module” portion of the algorithm used to obtain the defect position, that is associated with the function of the “obtaining unit”, as is disclosed in figure 3 and paragraphs 94-117, and summarized in claims 15-18. Therefore, independent claim 11 is considered to be in condition for allowance.
Any comments considered necessary by applicant must be submitted no later than the payment of the issue fee and, to avoid processing delays, should preferably accompany the issue fee. Such submissions should be clearly labeled “Comments on Statement of Reasons for Allowance.”
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. See attached PTO-892.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AARON W CARTER whose telephone number is (571)272-7445. The examiner can normally be reached 8am - 5pm (Mon - Fri).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Villecco can be reached at (571) 272-7319. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/AARON W CARTER/Primary Examiner, Art Unit 2661