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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Preliminary Amendment
3. Preliminary amendment filed on 9/28/23 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/18/23, 6/11/24, 3/25/25, 4/16/25, 6/11/25, 8/27/25,11/26/25, the information disclosure statement was considered by initialing the PTO Form 1449.
Drawings
5. The Examiner has approved drawings filed on 9/28/23 .
Claim Interpretation
6. 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.
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 section” , “determining section”, “reliability determining section ” in claims 1, 5, 6.
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 § 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.
Claims 1 -3, 7- 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Senshu et al., ( JP 2015130093 A) in view of Nagai Kiyohiko (WO 2020031984 A1).
As to claim 1, Senshu discloses an information processing device (abstract) comprising: an obtaining section that obtains an output value given in response to inputting a target image into a classification model generated by carrying out learning ( see para 23, 39, 73) so that distances between feature ( see para 19, 39) quantities extracted from a first image group having a common feature (see para 12 features refers to vector data of numerical values that represent the properties of an image) become small ( see para 44) , when the feature quantities are embedded in a feature space ( see para 26 , 40) describe that the object recognition is performed using a case dictionary in which the image group of the same class is trained so that the feature vectors are located close each other in the measurement space (refer to paragraphs 0017 - 0024); and
Senshu fails to teach a determining section that applies, on a basis of the output value, a first method for the first image group or a second method for a second image group, which is constituted by an image not belonging to the first image group, to determine a given determination matter relating to the target image.
Nagai Kiyohiko discloses component inspection method and inspection system. The system comprises of : a determining section that applies, on a basis of the output value, a first method (note, first method corresponds to image data that is normal see para 13, 16, see para 46 the input image data is compared with the output image data (S3), and it is determined whether the two are within the same range (S4). If it is determined that they are within the same range (Yes), it is determined that the image data is normal, and the test result of "normal" is output to and stored in the test result data memory unit 123 (S5), see fig 5), also ( see fig 5, see para 22, see para 45-47 ) for the first image group or a second method values (see para 60- 63 ) in the target image ( note, second method corresponds to abnormal image data, see fig 5, see para 47 If it is not determined to be within the same range (No), it is determined to be abnormal image data, and the inspection result of "abnormal" is output to and stored in the inspection result data storage unit 123 (S6), and the processing ends ) , for a second image group ( see fig 5, see para 25, see para 45-47) , which is constituted by an image not belonging to the first image group, to determine a given determination matter relating to the target image ( see para 34, the image data taken for inspection is input as input data into the trained model (inspection model), and if the output data is within the same range as the input data, it is judged as "normal," and if it is not within the same range, it is judged as "abnormal." , see para 59, removing noise using GAN ), also see para 36 the inspection device 1 of this system pre-loads normal image data as training data, inputs the normal image data into an autoencoder, which is a type of deep learning neural network (DNN), performs image processing such as brightness mapping display, encodes the data, compresses it, and decodes (restores) it to generate reproduced image data, and then trains the device so that the normal image data (input data) and reproduced image data (output data) become the same image data, thereby generating (constructing) a trained model (inspection model/AI model).
It would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to have modify Senshu by the teaching first image group or a second method for a second image group, which is constituted by an image not belonging to the first image group, to determine a given determination matter relating to the target image as taught by Kiyohiko to component inspection method, and more particularly to a component inspection method and system for detecting abnormalities in images of components of approximately the same shape taken from a predetermined position ( as suggested by Kiyohiko see para 1).
As to claim 2, Kiyohiko disclose the information processing device according to claim 1, wherein: the first image group is an image group for which determination on a basis of an output value given in response to inputting the target image ( see para 10,11 ) into a learned model generated by machine learning is effective ( see para 19, 36, 49) ;
the first method includes at least a process of determining the determination matter with use of the learned model (note, first method corresponds to image data that is normal see para 13, 16, see para 46 the input image data is compared with the output image data (S3), and it is determined whether the two are within the same range (S4). If it is determined that they are within the same range (Yes), it is determined that the image data is normal, and the test result of "normal" is output to and stored in the test result data memory unit 123 (S5), see fig 5) ; and
the second method includes at least a process of determining the determination matter through numerical analysis of pixel values (see para 60- 63 ) in the target image ( note, second method corresponds to abnormal image data, see fig 5, see para 47 If it is not determined to be within the same range (No), it is determined to be abnormal image data, and the inspection result of "abnormal" is output to and stored in the inspection result data storage unit 123 (S6), and the processing ends ) .
Regarding claim 3, it is interpreted and thus rejected for the same reasons as applied above in the rejection of claim 2.
Regarding claim 7, it is interpreted and thus rejected for the same reasons as applied above in the rejection of claim 1.
As to claim 8, Kiyohiko teaches a computer-readable, non-transitory storage medium in which a determination program is stored, the determination program causing a computer to function as an information processing device recited in claim 1, the determination program causing the computer to function as the obtaining section and the determining section ( fig 1, page 3 para 7, the control unit 11 reads the processing program stored in the storage device 12 and executes the inspection processing ).
Allowable Subject Matter
Claims 4 – 6, 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.
Other prior art cited
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US. Patent Number: 20190290246, 20140202937, 20200226744, 20060219013.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHEELA C CHAWAN whose telephone number is (571)272-7446. The examiner can normally be reached M- F 8 am -5.00 pm Flex.
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/SHEELA C CHAWAN/ Primary Examiner, Art Unit 2669