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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/09/2025, 08/28/2025, 02/29/2025 and 02/26/2025 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 limitations are: “image obtaining module”, “image analysis module”, “region extraction module” and “defect analysis module” in claim 16
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 § 112(b)
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.
Claim 16 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as failing to set forth the subject matter which the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the applicant regards as the invention.
Regarding Claim 16, the claim limitations “image analysis module”, “region extraction module” and “defect analysis module” in claim 16 invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function.
Regarding the “image analysis module”, the applicant appears to describe the “image analysis module” in paragraph 0124 of the publication of the specification that as reference number 200 in Figure 11. Applicant further describes the “image analysis module” in paragraphs 0126, 0129 and 0130-135. However, none of these paragraphs describe a structure for the “image analysis module”. It is not even clear if the “image analysis module” is a structure or computer implemented 112(f) limitation, which requires a structure (usually a storage medium) and a specific algorithm. The “image analysis module” is merely shown as a black box in Figure 11 and there is nothing in the specification that would imply a structure for the “image analysis module”, or that the “image analysis module” is a computer-implement 112(f) limitation. Therefore, in this instance “image analysis module” is interpreted as a 112(f) limitation and the specification fails to disclose a specific structure for the “image analysis module”.
Regarding the “region extraction module”, the applicant appears to describe the “region extraction module”, in paragraph 0124 of the publication of the specification that as reference number 300 in Figure 11. Applicant further describes the “region extraction module”, in paragraphs 0127 and 0136. However, none of these paragraphs describe a structure for the “region extraction module” It is not even clear if the “region extraction module” is a structure or computer implemented 112(f) limitation, which requires a structure (usually a storage medium) and a specific algorithm. The “region extraction module” is merely shown as a black box in Figure 11 and there is nothing in the specification that would imply a structure for the “region extraction module”, or that the “region extraction module” is a computer-implement 112(f) limitation. Therefore, in this instance “region extraction module” is interpreted as a 112(f) limitation and the specification fails to disclose a specific structure for the “region extraction module”.
Regarding the “defect analysis module”, the applicant appears to describe the “defect analysis module” in paragraph 0124 of the publication of the specification that as reference number 400 in Figure 11. Applicant further describes the “defect analysis module” in paragraphs 0128 and 0137-0142. However, none of these paragraphs describe a structure for the “defect analysis module” It is not even clear if the “defect analysis module” is a structure or computer implemented 112(f) limitation, which requires a structure (usually a storage medium) and a specific algorithm. The “defect analysis module” is merely shown as a black box in Figure 11 and there is nothing in the specification that would imply a structure for the “defect analysis module”, or that the “defect analysis module” a computer-implement 112(f) limitation. Therefore, in this instance “defect analysis module” is interpreted as a 112(f) limitation and the specification fails to disclose a specific structure for the “defect analysis module”.
Therefore, the claim is indefinite and is rejected under 35 U.S.C. 112(b) or pre-AIA 35
U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation
under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure,
material, or acts disclosed therein to the function recited in the claim, without
introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the
corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are
implicitly or inherently set forth in the written description of the specification, perform
the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
Claim Rejections - 35 USC § 112(a)
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.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
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 of carrying out his invention.
Claim 16 is 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 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 applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention
Regarding claim 16, applicant claims, “an image analysis module configured to determine an insulation coating region and a tab region in the electrode plate image; a region extraction module configured to determine a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region; and a defect analysis module configured to perform defect detection on the defect detection region to obtain a defect detection result.” As per MPEP § 2181(IV), “A means- (or step-) plus-function limitation that is found to be indefinite under 35 U.S.C. 112(b) based on failure of the specification to disclose corresponding structure, material or act that performs the entire claimed function also lacks adequate written description” (emphasis added).
Furthermore, as per MPEP 2163.03(VI), “(s)uch a limitation also lacks an adequate written description as required by 35 U.S.C. 112(a) or pre-AIA 35 U.S.C. 112, first paragraph, because an indefinite, unbounded functional limitation would cover all ways of performing a function and indicate that the inventor has not provided sufficient disclosure to show possession of the invention.” Therefore, since applicant has not defined any particular structure for the “image analysis module” in claim 16, “region extraction module” in claim 16 and “defect analysis module” in claim 16 the inventor has not provided sufficient disclosure to show possession of the invention. Applicant has not provided any specific definition for the structure that carry out the functions disclosed in claim 8. Additionally, the claimed invention as a whole may not be adequately described if the claims require an essential or critical feature which is not adequately described in the specification and which is not conventional in the art or known to one of ordinary skill in the art. It appears that these components and/or features are essential and critical features of the applicants invention because without them applicant’s invention wouldn’t work. In particular, the structure of the image analysis module, region extraction module and defect analysis module are not described in any detail. Therefore, since applicant has not adequately described a particularly structure for performing each of the functions, a person skilled in the art at the time the invention was filed would not have recognized that the inventor was in possession of the invention as claimed.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3, 5 and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng et al. ("CN 113313711 A") in view of Ma et al. ("CN 111681241 A").
Regarding Claim 1, Zheng teaches a method for detecting a defect on an insulation coating on a battery electrode plate, comprising: obtaining an electrode plate image obtained by photographing an electrode plate(Abstract, “the device comprises an image sensor, an MCU module, an FPGA module, a communication module and a CameraLink interface module; the image sensor collects the image data of the pole piece and sends it to the FPGA module;”, Figure 1, also shows a camera system for imaging the lithium battery pole piece), wherein the electrode plate image comprises at least one complete electrode plate; (Page 6, Paragraph 9, “Referring to FIG. 3, in some embodiments, it further claims a lithium battery pole piece width detection system, comprising at least one frame 200, each frame 200 is provided with at least one of the camera 100, each camera 100 the width information detected is insulating coating dressing width, the tab white width; pole piece coating area width, one of the whole width of the current collector.”, as disclosed in the prior art the battery image contains a complete electrode plate as further shown in figure 4 and 5. )determining an insulation coating region and a tab region in the electrode plate image (Page 6, Paragraph 10, “Specifically, referring to FIG. 4 and FIG. 5, the anode pole piece as shown in FIG. 4, A area is pole ear white area, B area is insulating coating dressing area, C area is coating area, D area is the whole current collector area; the negative pole piece is shown in FIG. 5, A area is tab white area, C area is coating area, D area is the whole current collector area.”, As shown in figure 4, the area labelled A is the tab region of the plate and B is the insulation coating area of the plate.); and performing defect detection on the defect detection region to obtain a defect detection result. (Page 6, Paragraph 7, “capable of performing edge detection and width calculation according to the collected image data, and sending the calculated width information to the upper computer, effectively reducing the load of the computer CPU, ensuring the real time of the width detection, but also capable of directly sending the image data to the upper computer through the CameraLink interface module; further performing defect detection, using two interface modules”, this section of the prior art discloses using a host computer that is in communication with the camera system to perform defect detection on the electrode plate image. )
Zheng does not explicitly disclose determining a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region;
Ma teaches determining a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region; (Page 2, Paragraphs 5-7, “S1 obtaining the image of the upper and lower surfaces of the material; S2, dividing the material image into a coating region and a non-coating region based on the image grey value; S3, identifying the defect of the coating area and the non-coating area; measuring the relative size of the coating on the material image”, in this section of the prior art, images of the electrode plate are used to determine where the defect is in the insultation coating region and non-coating regions using pixel data.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng with Ma in order to use pixel data to determine defects in the coating and non-coating regions of the electrode plate. One skilled in the art would have been motivated to modify Zheng in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 2, the combination of Zheng and Ma teach the method according to claim 1, where Zheng teaches wherein the determining an insulation coating region and a tab region in the electrode plate image comprises: performing full-image edge finding on the electrode plate image to obtain a primary positioning electrode plate edge; (Page 2, Paragraph 9, “the FPGA module further comprises an edge detection module for filtering the image data, the image after filtering processing and the transverse edge operator plane convolution processing, obtaining the transverse edge intensity of each pixel position in the image according to the pixel gray scale of the edge position peripheral region. setting the transverse edge intensity of the pixel position of the grey value outside the preset range 0; accumulating and overlapping the transverse edge intensity of each pixel position of each row of pixels of the preset row number; and obtaining the pixel position of the maximum value of the transverse edge intensity in the edge region” as disclosed in this section, edge detection is used to filter the image data based on the maximum intensity value of pixel data in order to determine a position of the edge of the electrode plate.)
Ma further teaches performing secondary positioning based on the primary positioning electrode plate edge to determine the insulation coating region in the electrode plate image; and performing searching based on the insulation coating region to determine the tab region in the electrode plate image. (Page 2, Paragraphs 6-8, “S2. through the image grey value, according to the aluminium foil base material on the material is white, coating is black for detecting region ROI (Region of interest) to locate, firstly determining the longitudinal boundary of the coating region and the non-coating region by means of global searching and linear fitting in the material travelling direction, so as to identify the transverse boundary of the coating area by the edge finding tool; the image is divided into a coating area and a non-coating area; S3, identifying the defect of the coating area and the non-coating area; measuring the related size of the coating on the material image.”, as disclosed in Paragraphs 6-8, determining a boundary of the coating and non-coating region is performed by using a global searching and linear fitting algorithm to define the edges of each region in the electrode image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng with Ma in order to perform a global search of the edges of the image to identify coating and non coating regions. One skilled in the art would have been motivated to modify Zheng in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 3, the combination of Zheng and Ma teach the method according to claim 2,
Zheng teaches wherein the performing full-image edge finding on the electrode plate image to obtain a primary positioning electrode plate edge(Page 2, Paragraph 9)
Ma further teaches performing the full-image edge finding on the electrode plate image in a direction toward a tab from one side away from the tab to obtain the primary positioning electrode plate edge. (Page 2, Paragraphs 10-11, “Step S2 comprises: through the image grey value, according to the aluminium foil base material on the material is white, coating is black for locating the detection area ROI;determining the longitudinal boundary of the coating area and the non-coating area by a global searching edge and a linear fitting manner in the material travelling direction; identifying the transverse boundary of the coating area by the edge finding tool; dividing the image into the coating area and the non-coating area.”, as disclosed in this section of the prior art, using pixel data of each the coating area and non-coating area , a global searching edge and linear fitting algorithm is performed in a traveling direction of the plate to determine the edge of the coating and non-coating regions of the plate.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng with Ma in order to use pixel color information to perform a global search of the edges of the image to identify coating and non coating regions. One skilled in the art would have been motivated to modify Zheng in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 5, the combination of Zheng and Ma teach the method according to claim 2, where Ma further teaches wherein the performing secondary positioning based on the primary positioning electrode plate edge to determine the insulation coating region in the electrode plate image(Page 2, Paragraphs 10-11 disclose performing edge finding to determining coating and non-coating regions in the electrode image.) comprises: determining a target insulation coating region based on the primary positioning electrode plate edge, and performing extraction on the target insulation coating region to determine the insulation coating region in the electrode plate image. (Page 2, Paragraph 10-12, “Step S2 comprises: through the image grey value, according to the aluminium foil base material on the material is white, coating is black for locating the detection area ROI; determining the longitudinal boundary of the coating area and the non-coating area by a global searching edge and a linear fitting manner in the material travelling direction; identifying the transverse boundary of the coating area by the edge finding tool; dividing the image into the coating area and the non-coating area. Step S3 comprises: the coating area and the non-coating area identify the defective pixel through the image pre-processing and the convolutional neural network algorithm;”, as disclosed in this section of the prior art, once the pixel data pertaining to coating and non-coating regions are determined an edge finding tool used to identify the boundaries of the region and then the image is divided into coating and non-coating regions and later used to perform defect detection using a CNN in step S3.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng with Ma in order to use pixel color information to perform a global search of the edges of the image to identify coating and non coating regions. One skilled in the art would have been motivated to modify Zheng in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 16, Zheng teaches an apparatus for detecting a defect on an insulation coating on a battery electrode plate, comprising: an image obtaining module(The module is being interpreted under 35 U.S.C 112(f) and the corresponding structure of the module appears to be disclosed in paragraphs 0049-0053, 0109 of the specification to be a camera in which the prior art discloses a camera system in Figure 1.) configured to obtain an electrode plate image obtained by photographing an electrode plate(Abstract, “the device comprises an image sensor, an MCU module, an FPGA module, a communication module and a CameraLink interface module; the image sensor collects the image data of the pole piece and sends it to the FPGA module;”, Figure 1, also shows a camera system for imaging the lithium battery pole piece), wherein the electrode plate image comprises at least one complete electrode plate(Page 6, Paragraph 9, “Referring to FIG. 3, in some embodiments, it further claims a lithium battery pole piece width detection system, comprising at least one frame 200, each frame 200 is provided with at least one of the camera 100, each camera 100 the width information detected is insulating coating dressing width, the tab white width; pole piece coating area width, one of the whole width of the current collector.”, as disclosed in the prior art the battery image contains a complete electrode plate as further shown in figure 4 and 5.); an image analysis module(This module was rejected under 35 U.S.C 112(a) & U.S.C 112 (b) and it is unclear from the specification the exact structure of this module and for the purposes of a prior art rejection the module will not be interpreted under 35 U.S.C 112(f)) configured to determine an insulation coating region and a tab region in the electrode plate image (Page 6, Paragraph 10, “Specifically, referring to FIG. 4 and FIG. 5, the anode pole piece as shown in FIG. 4, A area is pole ear white area, B area is insulating coating dressing area, C area is coating area, D area is the whole current collector area; the negative pole piece is shown in FIG. 5, A area is tab white area, C area is coating area, D area is the whole current collector area.”, As shown in figure 4, the area labelled A is the tab region of the plate and B is the insulation coating area of the plate. ); and a defect analysis module(This module was rejected under 35 U.S.C 112(a) & U.S.C 112 (b) and it is unclear from the specification the exact structure of this module and for the purposes of a prior art rejection the module will not be interpreted under 35 U.S.C 112(f)) configured to perform defect detection on the defect detection region to obtain a defect detection result. (Page 6, Paragraph 7, “capable of performing edge detection and width calculation according to the collected image data, and sending the calculated width information to the upper computer, effectively reducing the load of the computer CPU, ensuring the real time of the width detection, but also capable of directly sending the image data to the upper computer through the CameraLink interface module; further performing defect detection, using two interface modules”, this section of the prior art discloses using a host computer that is in communication with the camera system to perform defect detection on the electrode plate image. )
Zheng does not explicitly disclose a region extraction module configured to determine a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region;
Ma teaches a region extraction module(This module was rejected under 35 U.S.C 112(a) & U.S.C 112 (b) and it is unclear from the specification the exact structure of this module and for the purposes of a prior art rejection the module will not be interpreted under 35 U.S.C 112(f)) configured to determine a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region; (Page 2, Paragraphs 5-7, “S1 obtaining the image of the upper and lower surfaces of the material; S2, dividing the material image into a coating region and a non-coating region based on the image grey value; S3, identifying the defect of the coating area and the non-coating area; measuring the relative size of the coating on the material image”, in this section of the prior art, images of the electrode plate are used to determine where the defect is in the insultation coating region and non-coating regions using pixel data.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng with Ma in order to use pixel data to determine defects in the coating and non-coating regions of the electrode plate. One skilled in the art would have been motivated to modify Zheng in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 17, the combination of Zheng and Ma teach the limitations of claim 1, where Zhang further teaches a computer device comprising a memory and a processor, wherein the memory stores a computer program; and the processor, when executing the computer program, implements steps of the method according to claim 1. (Page 5, Paragraph 7, “FPGA module 3 receives the image data, on the one hand, after the CameraLink coding module 32 for coding processing through the CameraLink interface module 5 to the upper computer, on the other hand the image data for processing and performing edge detection and width calculation. Specifically, the FPGA module 3 further comprises a data pre-processing module 33 and a data decoding module 34, a data pre-processing module 33 for pre-processing the image data; the data decoding module 34 is used for decoding the pre-processed image data.”, as disclosed in this section an FPGA(Field-Programmable Gate Array) is a reconfigurable hardware device capable of storing software code to execute and it is coupled to a host computer which inherently would contain a memory and processor. )
Regarding Claim 18, the combination of Zheng and Ma teach the limitations of claim 1, where Zheng further teaches a non-transitory computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements steps of the method according to claim 1. (Page 5, Paragraph 7, discloses an FPGA(Field-Programmable Gate Array) is a reconfigurable hardware device capable of storing software code to execute and it is coupled to a host computer which inherently would contain a memory and processor.)
Regarding Claim 19, the combination of Zheng and Ma teach the limtiations of claim 1, where Zheng further teaches a system for detecting a defect on a battery electrode plate(Fig. 1), comprising an image obtaining apparatus(Referring to FIG. 1, in some embodiments, providing a lithium battery pole piece width detection of the camera, comprising an image sensor 1,) and a host computer, wherein the image obtaining apparatus is configured to obtain an electrode plate image obtained by photographing an electrode plate, and send the electrode plate image to the host computer (Page 5, Paragraph 1, “the image sensor 1 is used for collecting the image data of the pole piece and sending to the FPGA module 3; the FPGA module 3 is used for processing the image data and sending the image data to the upper computer through the CameraLink interface module 5”, Page 5, Paragraph 1 discloses using a FPGA module to send image data obtained to a host computer.), and the host computer is configured to detect a defect on an insulation coating on the battery electrode plate by using the method according to claim 1. (Page 5, Paragraph 3, “edge detection and width calculation according to the collected image data, and the calculated width information is sent to the upper computer, on the other hand; further capable of directly sending the image data to the upper computer through the CameraLink interface module, further performing defect detection, using two interface modules”, Page 5, Paragraph 3 Discloses the host computer processes the image data and performs defect detection on the image data. )
Claims 6-8 are rejected under 35 U.S.C. 103 as being unpatentable over Zheng et al. ("CN 113313711 A") in view of Ma et al. ("CN 111681241 A") in view of Wang et al. ("CN 114022418 A").
Regarding Claim 6, while the combination of Zheng and Ma teach the method according to claim 2, they do not explicitly teach wherein the performing searching based on the insulation coating region to determine the tab region in the electrode plate image comprises: performing secondary region positioning based on the insulation coating region to determine a target tab detection region; and finding and extracting the tab region in the target tab detection region.
Wang teaches wherein the performing searching based on the insulation coating region to determine the tab region in the electrode plate image comprises: performing secondary region positioning based on the insulation coating region to determine a target tab detection region; and finding and extracting the tab region in the target tab detection region.
(Page 6, Paragraph 4-6, “according to the defect edge, using the minimum external rectangular method to calibrate the defect profile; As shown in FIG. 2 and FIG. 10, the embodiment of the industrial camera to obtain two pieces of lithium battery image containing pole piece defect, wherein the pole piece in FIG. 2 there is metal leakage defect, FIG. 9 in pole piece has nick defect; According to FIG. 2 and FIG. 10, the image ROI extraction algorithm for extracting lithium battery pole piece image, eliminating the pole piece defect of lithium battery image in the tab region and bottom background region of the influence, correspondingly obtaining FIG. 3 and FIG. 11.”, as disclosed in this section of the prior art, a defect is determined in the lithium battery image and an image ROI extraction is performed to extract the tab region in which the defect is located in the image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng and Ma with Wang in order to extract the tab region in the case of a defect in the image. One skilled in the art would have been motivated to modify Zheng and Ma in this manner in order to allow for fast calculation speed, high accuracy and good segmentation effect. (Wang, Abstract)
Regarding Claim 7, the combination of Zheng, Ma and Wang teach the method according to claim 6, where Ma further teaches wherein the performing secondary region positioning based on the insulation coating region to determine a target tab detection region comprises: extracting a primary positioning insulation edge of the insulation coating region and determining the target tab detection region based on the primary positioning insulation edge.(Page 2, Paragraphs 6-7, “S2. through the image grey value, according to the aluminium foil base material on the material is white, coating is black for detecting region ROI (Region of interest) to locate, firstly determining the longitudinal boundary of the coating region and the non-coating region by means of global searching and linear fitting in the material travelling direction, so as to identify the transverse boundary of the coating area by the edge finding tool; the image is divided into a coating area and a non-coating area; S3, identifying the defect of the coating area and the non-coating area; measuring the related size of the coating on the material image.”, Paragraph 6-7 disclose using pixel data to determine the edges of the coating and non-coating region in order to divide the image into a coating and non-coating regions for defect detection.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng and Wang with Ma in order to use pixel color information to perform a global search of the edges of the image to identify coating and non coating regions. One skilled in the art would have been motivated to modify Zheng and Wang in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Regarding Claim 8, the combination of Zheng, Ma and Wang teach the method according to claim 6, where Ma further teaches wherein the finding and extracting the tab region in the target tab detection region comprises: extracting a region having a tab gray feature in the target tab detection region to obtain a primary tab region (Page 2, Paragraph 6, “S2. through the image grey value, according to the aluminium foil base material on the material is white, coating is black for detecting region ROI (Region of interest) to locate, firstly determining the longitudinal boundary of the coating region and the non-coating region by means of global searching”, in this section of the prior art, image grey value is used to determine regions of interest to locate in the image pertaining to coating and non coating regions.) ; and determining, based on a region shape and a region size of the primary tab region, whether the primary tab region comprises a tab, and if the primary tab region comprises a tab, determining that the tab region is obtained. (Page 4, Second to Last Paragraph, “Defect detection: coating area and non-coating area by image pre-processing and convolutional neural network algorithm to identify the defective pixel, forming a defect picture. according to the defect length, width, grey value, shape feature, grey range and so on to classify the defect, scoring according to the severity level of the defect, if the number of some serious defect in the unit length exceeds the set threshold value, judging that it is unqualified product.”, as disclosed in this section, a CNN is used to determine where the defect is in the image region based on the grey value, shape and defect length and width in the image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng and Wang with Ma in order to use grey value to determine a region of interest in the image to perform defect detection. One skilled in the art would have been motivated to modify Zheng and Wang in this manner in order to provide a quality control method and system based on machine vision detection and measurement depth integration. (Ma, Abstract)
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Zheng et al. ("CN 113313711 A") in view of Ma et al. ("CN 111681241 A") in view of Hong et al. US PG-Pub(US 20230327222 A1).
Regarding Claim 10, while the combination of Zheng and Ma teach the method according to claim 1, they do not explicitly teach wherein the performing defect detection on the defect detection region to obtain a defect detection result comprises: performing connected component extraction on the defect detection region; and when a connected component similar to a predetermined defect region exists, determining that a defect exists; and the defect detection result comprises defect existence information.
Hong teaches wherein the performing defect detection on the defect detection region to obtain a defect detection result comprises: performing connected component extraction on the defect detection region; and when a connected component similar to a predetermined defect region exists, determining that a defect exists; and the defect detection result comprises defect existence information (¶[0028] “a first step of determining a plurality of surfaces for performing an appearance inspection of manufactured and activated lithium secondary battery, dividing each of the plurality of surfaces into one or more regions for each type of defects and accumulating first image data for each of these regions; [0029] a second step of constructing a second image data including existing image data in which normal or defective is confirmed according to the type of defects occurring in each region; a third step of comparing the first and second image data with each other in an artificial neural network to first judging whether the lithium secondary battery is normal or defective;”, ¶[0028]-¶[0029] discloses dividing the image into a plurality of regions that have defects and using a neural network to compare images of known defects or normal images to the present to determine if a defect exists in the battery image.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng and Ma with Hong in order to compare the current image to a predetermined image of a defect. One skilled in the art would have been motivated to modify Zheng in this manner in order to improve the reliability, accuracy and reproducibility of inspection results by advancing the artificial neural network learning according to each divided region and the type of defects occurring in each region. (Hong, ¶[0002])
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Zheng et al. ("CN 113313711 A") in view of Ma et al. ("CN 111681241 A") in view of Tang et al. (WO 2022052480 A1).
Regarding Claim 15, while the combination of Zheng and Ma teach the method according to claim 1, they do not explicitly teach wherein after the performing defect detection on the defect detection region to obtain a defect detection result, the method further comprises: binding the defect detection result with electrode plate identification information.
Tang teaches wherein after the performing defect detection on the defect detection region to obtain a defect detection result, the method further comprises: binding the defect detection result with electrode plate identification information (Page 6, Second to Last Paragraph, “In S6, image display: display the image with flaws on the screen, and store the image with flaws. In one embodiment, the images with flawed features are not only displayed on the software interface window in real time, but also saved in a specified folder according to the naming format specified by the user, and the results of the flaw classification statistics are saved in real time. Under the specified folder, the saved local data is convenient for users to observe and trace defects.”, as disclosed in this section of the prior art, once a flaw in the lithium battery is determined it is displayed and stored in the memory of the system.)
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the claimed invention as taught by Zheng and Ma with Tang in order to store the defect detection of the electrode plate. One skilled in the art would have been motivated to modify Zheng and Ma in this manner in order to automatically classify and process the defects, eliminate the response delay of images and processing devices (Tang, Page 2, Paragraph 2)
Allowable Subject Matter
Claims 4, 9 and 11-14 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.
Regarding Claim 4, the primary reason for the allowance of the claim is the inclusion of the limitations, “wherein the performing the full-image edge finding on the electrode plate image in a direction toward a tab from one side away from the tab to obtain the primary positioning electrode plate edge comprises: performing the full-image edge finding on the electrode plate image in the direction toward the tab from the side away from the tab; and when a predetermined sudden change edge is found, determining that the edge finding succeeds, and determining the found predetermined sudden change edge as the primary positioning electrode plate edge.”, in all the claim which is not found in the prior art references. It is noted that the examiner has not found any other prior art to anticipate or obviate the quoted claim limitations supra, when read in light/combination of the other claimed limitations within the cited claim. Also, it is noted that the quoted limitations, in combination with the other claim limitations of the cited claim, deem the claim patentable, not just the consideration of the quoted limitations by themselves.
Regarding Claim 9, the primary reason for the allowance of the claims is the inclusion of the limitations, “wherein the determining a defect detection region in the insulation coating region in the electrode plate image based on the insulation coating region and the tab region comprises: performing edge finding on the tab region to obtain a tab edge; obtaining an electrode plate edge based on the tab edge and preset distance data, wherein the preset distance data is distance data between the tab edge and the electrode plate edge; and determining the defect detection region in the insulation coating region in the electrode plate image based on the primary positioning electrode plate edge, the primary positioning insulation edge, and the electrode plate edge.”, in all the claim which is not found in the prior art references. It is noted that the examiner has not found any other prior art to anticipate or obviate the quoted claim limitations supra, when read in light/combination of the other claimed limitations within the cited claim. Also, it is noted that the quoted limitations, in combination with the other claim limitations of the cited claim, deem the claim patentable, not just the consideration of the quoted limitations by themselves.
Regarding Claim 11, the primary reason for the allowance of the claims is the inclusion of the limitations, “wherein the performing defect detection on the defect detection region to obtain a defect detection result further comprises: when the connected component similar to the preset defect region does not exist, calculating a coating region misalignment value of the electrode plate; and the defect detection result comprises defect non-existence information and the coating region misalignment value.”, in all the claim which is not found in the prior art references. It is noted that the examiner has not found any other prior art to anticipate or obviate the quoted claim limitations supra, when read in light/combination of the other claimed limitations within the cited claim. Also, it is noted that the quoted limitations, in combination with the other claim limitations of the cited claim, deem the claim patentable, not just the consideration of the quoted limitations by themselves.
Regarding Claim 12-14, these claims would be allowed by virtue of dependency.
Conclusion
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/HAN HOANG/Primary Examiner, Art Unit 2661