DETAILED ACTION
Claims 1-16 are pending in this application and being examiner under the priority date of 12/21/2023 in accordance with the applicant’s claim for foreign priority.
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.
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 1-16 are rejected under 35 U.S.C. 101 because they are drawn to an abstract idea, mental process or step of mere data gathering without significantly more.
Regarding claim 1, 9 and 16, claims recite the following limitations, which are drawn to either an abstract idea, mental process or step of mere data gathering as noted by the examiner; “An apparatus for diagnosing a battery, the apparatus comprising:
a processor (Additional Element);
and a memory configured to store instructions that, when executed by the processor, cause the processor to (Additional Element):
generate a two-dimensional (2D) flat image in which a three-dimensional (3D) image of the battery is spread out (Step of mere data gathering);
divide the 2D flat image into a plurality of zones (mental process by which a human could manually divide and image);
and diagnoses the battery based on changes in pixel values between the plurality of zones (Mental process by which a human could assess and image and determine changes across zone to determine and diagnosis).”
Under step 2A prong 1, the claim limitations recited by claims 1, 9 and 16 are drawn to either a step of mere data gathering, mental process or abstract idea as noted above. Further, under step 2A prong 2, the claim recites the additional elements of a memory and a processor, which fail to integrate the judicial exceptions recited into practical application or amount to significantly more. Under step 2B, the claim does not include any limitations or additional elements which translate the claim into practical application or amount to significantly more. (see MPEP 2106)
Dependent claims 2-8 and 10-15 follow the same logic, and are therefore also rejected as being drawn to an abstract idea without significantly more.
Regarding claim 2 and claim 10, the claims recite; “wherein the processor is configured to generate a cross-sectional image of the battery from the 3D image of the battery (Step of mere data gathering with the additional element of the processor),
to plot a plurality of points according to pixel values of the generated cross-sectional image on the cross-sectional image to generate plot data in which at least some of the points are rounded (Mental process of data gathering/generation by which a human could reasonably plot pixel data manually),
and to generate the 2D flat image by linearizing the generated plot data. (Mental process of data gathering/generation by which a human could reasonably linearize pixel data)”
The above limitations are drawn to either a mental process or step of mere data gathering, and include the additional element of a processor which is recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 3, and claim 11, the claims recite; “wherein, as a process for identifying the changes in pixel values between the plurality of zones, the processor is configured to identify a plurality of peak positions where peaks of the pixel values appear in each zone, and wherein the plurality of peak positions have values normalized based on a specific position of the 2D flat image. (Mental process of performing math of pixel data values, which a human could reasonably perform)”
The above limitations are drawn to either a mental process or step of mere data gathering, and include the additional element of a processor which is recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 4 and claim 12 the claims recite; “ wherein a process for analyzing changes in peaks of a pixel value corresponding to a specific peak position that appear across the plurality of zones is defined as a peak change analysis process, and wherein the processor is configured to repeatedly perform the peak change analysis process on each of the plurality of peak positions and then to diagnose the battery based on results of the repeated performance. (Mental process of performing math of pixel data values, which a human could reasonably perform)”
The above limitations are drawn to either a mental process or step of mere data gathering, and include the additional element of a processor which is recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 5 and 13, the claims recite; “wherein the processor is configured to diagnose deformation of an internal structure of the battery by analyzing a change rate of peaks of the pixel value corresponding to each peak position that appears across a diagnosis target section within the plurality of zones (Mental process of assessing pixel value data and determining a change)”
The above limitations are drawn to either a mental process or step of mere data gathering, and include the additional element of a processor which is recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 6, and claim 14, the claims recite; “ wherein the processor is configured to determine that the deformation of the internal structure of the battery has occurred at a peak position corresponding to an outlier change rate among a plurality of change rates for each peak position. (Mental process of performing math of pixel data values, which a human could reasonably perform)”
The above limitations are drawn to either a mental process or step of mere data gathering, and include the additional element of a processor which is recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 7 and claim 15, the claims recite; “wherein the diagnosis target section is a section excluding a saturation section in which the change rate of the peaks of the pixel value corresponding to each peak position is saturated from the plurality of zones. (Mental process of performing math of pixel data values, which a human could reasonably perform)”
The above limitations are drawn to either a mental process or step of mere data gathering, and recited with a high level of generality and does not translate the claims into significantly more than an abstract idea.
Regarding claim 8, the claim recites “The apparatus of claim 1, wherein the 3D image of the battery comprises a computed tomography (CT) image, and the pixel values are greyscale intensities of the CT image. (step of mere data gathering)”
The above limitations are drawn to either a mental process or step of mere data gathering, and recited with a high level of generality and does not translate the claim into significantly more than an abstract idea.
Claim 16 is rejected under 35 U.S.C. 101 as being drawn to computer readable medium.
Regarding claim 16, the claim recites the use of computer readable medium. A "computer readable storage medium" is defined in the specification to include “include a ROM, a RAM, magnetic media such as a hard disk, a floppy disk, and a magnetic tape, optical media such as a compact disc read-only memory (CD-ROM) and a digital video disc (DVD), magneto-optical media such as a floptical disk, and a hardware device such as a flash memory, that is specially made to store and perform program instructions” (See applicant’s specification, [00131]). The broadest reasonable interpretation of a claim drawn to a computer readable medium (also called machine readable medium and other such variations) typically covers forms of non-transitory tangible media and transitory propagating signals per se in view of the ordinary and customary meaning of computer readable media. See MPEP 2111.01. When the broadest reasonable interpretation of a claim covers a signal per se, the claim must be rejected under 35 U.S.C 101 as covering non-statutory subject matter. The claims, as defined in the specification, cover both non-statutory subject matter and statutory subject matter. A claim drawn to such a computer readable medium that covers both transitory and non-transitory embodiments may be amended to narrow the claim to cover only statutory embodiments by adding the limitation "non-transitory" to the claim.
Claim 16 is rejected under 35 U.S.C. 101 as being drawn to a program per-se.
Regarding claim 16, claim 16 is directed to a program per se. Such claimed computer programs do not define any structural and functional interrelationships between the computer program and other claimed elements of a computer which permit the computer program’s functionality to be realized. In contrast, a claimed computer-readable medium encoded with a computer program is a computer element which defines structural and functional interrelationships between the computer program and the rest of the computer which permit the computer program’s functionality to be realized, and is thus statutory. See Lowry, 32 F.3d at 1583-84, 32 USPQ2d at 1035. Since a computer program is merely a set of instructions capable of being executed by a computer, the computer program, per se, is nonstatutory,
Claim Rejections - 35 USC § 112
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 1 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim 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. Claim 1 recites the limitation of a “two-dimensional image flat image where a three-dimensional image of a battery is spread out”. It is unclear what is meant by the image being “spread out”, for the purposes of examination, the examiner is interpreting the 2D image as being a cross-section of the 3D battery image. The applicant is encouraged to amend to clarify.
Claim 2 is rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim 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. The claim recites the limitation of points being “rounded”, it is unclear whether the applicant intends this to mean numerically rounded, or rounded in shape based on what is disclosed in specification paragraph [0076] and [0081]. For examiner purposes, the examiner is interpreting this limitation to mean the point values are numerically rounded. The applicant is encouraged to amend to clarify.
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.
6. Claims 1-2, 9-10 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20260011796 A1) in view of Wegner (US 20240097215 A1).
Regarding claim 1 Kim discloses; An apparatus for diagnosing a battery, the apparatus comprising (Kim, [0008] the system is a battery cell inspection system):
a processor (Kim, [0052] the system has a processor which processes data such as a CPU, MPU or MCU);
and a memory configured to store instructions that, when executed by the processor, cause the processor to (Kim, [0052] the processor is connected to a memory):
generate a two-dimensional (2D) flat image in which a three-dimensional (3D) image of the battery is spread out (Kim, [0010] the system is a battery cell inspection system which obtains 3D images of the battery, and cross section images of the batter (2D images));
divide the 2D flat image into a plurality of zones (Kim, [0044] regions of interest of battery may be individually photographed (dividing into zones), [0048] the different portions of the battery may have corresponding regions of interest for imaging inspection);
[and diagnoses the battery based on changes in pixel values between the plurality of zones.]
Kim does not disclose; and diagnoses the battery based on changes in pixel values between the plurality of zones.
However, in the same field of endeavor of battery inspection, Wegner discloses;
and diagnoses the battery based on changes in pixel values between the plurality of zones (Wegner, [0064] all pixels in all regions of an x-ray image of a battery are inspected and grouped by similarity to determine they belong to different features, [0066] patterns of the pixels is compared to pixel patterns for good features, and if it does not match a defect in the battery is diagnosed, for example, a weld pixel pattern is compared for a region to diagnose a good or bad weld).
The combination of Kim and Wegner would have been obvious to one ordinary skill in the art prior to the effective filing date of the presently claimed invention. Kim teaches a method of battery defect inspection using cross sectional images which may be reconstructed into a 3D image to asses internal component damage. Wegner teaches a method of x-ray battery inspection where pixels are grouped based on similarity to determine battery feature, and then compared to determine if a defect is present. The motivation for the addition of the pixel comparison feature of Wegner to the system of Kim is that this would improve the speed and accuracy of defect detection by automatically determining defects based on pixel analysis. (Wegner [0004]-[0018])
Regarding claim 2 the combination of Kim and Wegner teaches; The apparatus of claim 1, wherein the processor is configured to generate a cross-sectional image of the battery from the 3D image of the battery (Kim, [0055] the system may generate cross sectional images of the battery from the 3D image),
to plot a plurality of points according to pixel values of the generated cross-sectional image on the cross-sectional image to generate plot data in which at least some of the points are rounded (Kim, [0051] the system may generate labeled data from the battery images and store them as points, [0055] cross-sectional images may have endpoints/points for specific features tracked for each cross section image, [0058] Figures 4a-4G shows multiple cross sectional images, where tracked endpoints/features are plotted/displayed on the cross sectional image to show where the endpoints are that being tracked to assess for defects, [0065] in cases where the coordinate value is less than a reference value the average values may be used to approximate the point values, which is functionally equivalent to rounding to approximate a value),
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(Kim, figure 4A, emphasis added)
and to generate the 2D flat image by linearizing the generated plot data (Kim, [0065] a line is set for the values of the electrodes as determined via image analysis, (linearizing the plot data), figure 4F shows this, this functionally equivalent to what is shown in figure 4C and described in [0082] of applicant’s specification where a line is drawn on the plot relative to the plotted data).
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(Kim, figure 4F)
Regarding claim 9 the combination of Kim and Wegner teaches; A method of diagnosing a battery, the method comprising:
generating, by a processor (Kim, [0052] the system has a processor which processes data such as a CPU, MPU or MCU), a two-dimensional (2D) flat image in which a three-dimensional (3D) image of the battery is spread out (Kim, [0010] the system is a battery cell inspection system which obtains 3D images of the battery, and cross section images of the batter (2D images));
dividing, by the processor (Kim, [0052] the system has a processor which processes data such as a CPU, MPU or MCU), the generated 2D flat image into a plurality of zones (Kim, [0044] regions of interest of battery may be individually photographed (dividing into zones), [0048] the different portions of the battery may have corresponding regions of interest for imaging inspection);
and diagnosing, by the processor, the battery based on changes in pixel values between the plurality of zones (Wegner, [0064] all pixels in all regions of an x-ray image of a battery are inspected and grouped by similarity to determine they belong to different features, [0066] patterns of the pixels is compared to pixel patterns for good features, and if it does not match a defect in the battery is diagnosed, for example, a weld pixel pattern is compared for a region to diagnose a good or bad weld).
The combination of Kim and Wegner would have been obvious to one ordinary skill in the art prior to the effective filing date of the presently claimed invention. Kim teaches a method of battery defect inspection using cross sectional images which may be reconstructed into a 3D image to assess internal component damage. Wegner teaches a method of x-ray battery inspection where pixels are grouped based on similarity to determine battery feature, and then compared to determine if a defect is present. The motivation for the addition of the pixel comparison feature of Wegner to the system of Kim is that this would improve the speed and accuracy of defect detection by automatically determining defects based on pixel analysis. (Wegner [0004]-[0018])
Regarding claim 10 the combination of Kim and Wegner teaches; The method of claim 9, wherein, in the generating of the 2D flat image, the processor is configured to generate a cross-sectional image of the battery from the 3D image of the battery (Kim, [0055] the system may generate cross sectional images of the battery from the 3D image),
to plot a plurality of points according to pixel values of the generated cross-sectional image on the cross-sectional image to generate plot data in which at least some of the points are rounded (Kim, [0051] the system may generate labeled data from the battery images and store them as points, [0055] cross-sectional images may have endpoints/points for specific features tracked for each cross section image, [0058] Figures 4a-4G shows multiple cross sectional images, where tracked endpoints/features are plotted/displayed on the cross sectional image to show where the endpoints are that being tracked to assess for defects, [0065] in cases where the coordinate value is less than a reference value the average values may be used to approximate the point values, which is functionally equivalent to rounding to approximate a value),
and to generate the 2D flat image by linearizing the generated plot data (Kim, [0065] a line is set for the values of the electrodes as determined via image analysis, (linearizing the plot data), figure 4F shows this, this functionally equivalent to what is shown in figure 4C and described in [0082] of applicant’s specification where a line is drawn on the plot relative to the plotted data).
Regarding claim 16 the combination of Kim and Wegner teaches; A computer program, which is coupled to hardware and stored in a computer-readable storage medium, for performing operations of (Kim, [0052] the system has a processor which processes data such as a CPU, MPU or MCU):
generating a two-dimensional (2D) flat image in which a three-dimensional (3D) image of a battery is spread out (Kim, [0010] the system is a battery cell inspection system which obtains 3D images of the battery, and cross section images of the batter (2D images));
dividing the generated 2D flat image into a plurality of zones (Kim, [0044] regions of interest of battery may be individually photographed (dividing into zones), [0048] the different portions of the battery may have corresponding regions of interest for imaging inspection);
and diagnosing the battery based on changes in pixel values between the plurality of zones (Wegner, [0064] all pixels in all regions of an x-ray image of a battery are inspected and grouped by similarity to determine they belong to different features, [0066] patterns of the pixels is compared to pixel patterns for good features, and if it does not match a defect in the battery is diagnosed, for example, a weld pixel pattern is compared for a region to diagnose a good or bad weld).
The combination of Kim and Wegner would have been obvious to one ordinary skill in the art prior to the effective filing date of the presently claimed invention. Kim teaches a method of battery defect inspection using cross sectional images which may be reconstructed into a 3D image to assess internal component damage. Wegner teaches a method of x-ray battery inspection where pixels are grouped based on similarity to determine battery feature, and then compared to determine if a defect is present. The motivation for the addition of the pixel comparison feature of Wegner to the system of Kim is that this would improve the speed and accuracy of defect detection by automatically determining defects based on pixel analysis. (Wegner [0004]-[0018])
Claims 3-4, 8, and 11-12 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20260011796 A1) in view of Wegner (US 20240097215 A1) and in further view of Cha (US 20250371696 A1).
Regarding claim 3 the combination of Kim and Wegner teaches; The apparatus of claim 1, wherein,
as a process for identifying the changes in pixel values between the plurality of zones (Wegner, [0064] all pixels in all regions of an x-ray image of a battery are inspected and grouped by similarity to determine they belong to different features, [0066] patterns of the pixels is compared to pixel patterns for good features, and if it does not match a defect in the battery is diagnosed, for example, a weld pixel pattern is compared for a region to diagnose a good or bad weld),
[the processor is configured to identify a plurality of peak positions where peaks of the pixel values appear in each zone,
and wherein the plurality of peak positions have values normalized based on a specific position of the 2D flat image. ]
The combination of Kim and Wegner would have been obvious to one ordinary skill in the art prior to the effective filing date of the presently claimed invention. Kim teaches a method of battery defect inspection using cross sectional images which may be reconstructed into a 3D image to asses internal component damage. Wegner teaches a method of x-ray battery inspection where pixels are grouped based on similarity to determine battery feature, and then compared to determine if a defect is present. The motivation for the addition of the pixel comparison feature of Wegner to the system of Kim is that this would improve the speed and accuracy of defect detection by automatically determining defects based on pixel analysis. (Wegner [0004]-[0018])
The combination of Kim and Wegner fails to teach;
the processor is configured to identify a plurality of peak positions where peaks of the pixel values appear in each zone,
and wherein the plurality of peak positions have values normalized based on a specific position of the 2D flat image.
However, in the same field of endeavor, Cha teaches;
the processor is configured to identify a plurality of peak positions where peaks of the pixel values appear in each zone (Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks),
and wherein the plurality of peak positions have values normalized based on a specific position of the 2D flat image (Cha, [0106] the system may use rule based defect region methods, where the pixels for an area are extracted, the average brightness/intensity for that region is taken and then the pixel whose value is most different from the average range is used to determine the region, where the examiner is interpreting this as a normalization based on the average, and the peak position being the normalized value which is the biggest change).
The combination of Kim, Wegner and Cha would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Regarding claim 4 the combination of Kim, Wegner and Cha teaches; The apparatus of claim 3, wherein a process for analyzing changes in peaks of a pixel value corresponding to a specific peak position that appear across the plurality of zones is defined as a peak change analysis process (Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks, where the system is identifying multiple peaks and changes in pixel values, therefore this is a peak change analysis process),
and wherein the processor is configured to repeatedly perform the peak change analysis process on each of the plurality of peak positions and then to diagnose the battery based on results of the repeated performance (Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks, where the system is identifying multiple peaks and changes in pixel values, therefore this is a peak change analysis process which can be repeatedly performed).
The combination of Kim, Wegner and Cha would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Regarding claim 8 the combination of Kim, Wegner and Cha teaches; The apparatus of claim 1, wherein the 3D image of the battery comprises a computed tomography (CT) image (Kim [0054] the 3D image may be a CT image),
and the pixel values are greyscale intensities of the CT image (Cha, [0091] Pixel white and dark values are used in determining the features).
The combination of Kim, Wegner and Cha would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Regarding claim 11 the combination of Kim, Wegner and Cha teaches; The method of claim 9, wherein, in the diagnosing of the battery, the processor is configured to identify a plurality of peak positions where peaks of the pixel values appear in each zone (Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks),
and wherein the plurality of peak positions have values normalized based on a specific position of the 2D flat image (Cha, [0106] the system may use rule based defect region methods, where the pixels for an area are extracted, the average brightness/intensity for that region is taken and then the pixel whose value is most different from the average range is used to determine the region, where the examiner is interpreting this as a normalization based on the average, and the peak position being the normalized value which is the biggest change).
The combination of Kim, Wegner and Cha would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Regarding claim 12 the combination of Kim, Wegner and Cha teaches; The method of claim 11, wherein, a process for analyzing changes in peaks of a pixel value corresponding to a specific peak position that appear across the plurality of zones is defined as a peak change analysis process(Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks, where the system is identifying multiple peaks and changes in pixel values, therefore this is a peak change analysis process),
and wherein the processor is configured to repeatedly perform the peak change analysis process on each of the plurality of peak positions and then to diagnose the battery based on results of the repeated performance (Cha, [0089] from the images at least one or multiple features can be determined (multiple feature regions) [0091] the image feature value may be a pixel peak white or peak dark value, indicating multiple features with multiple peaks, where the system is identifying multiple peaks and changes in pixel values, therefore this is a peak change analysis process which can be repeatedly performed).
The combination of Kim, Wegner and Cha would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Claims 5-6 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20260011796 A1) in view of Wegner (US 20240097215 A1) and in further view of Cha (US 20250371696 A1) and Vu (US 20230237634 A1).
Regarding claim 5 the combination of Kim, Wegner and Cha fails to teach; The apparatus of claim 4, wherein the processor is configured to diagnose deformation of an internal structure of the battery by analyzing a change rate of peaks of the pixel value corresponding to each peak position that appears across a diagnosis target section within the plurality of zones.
However, in the same field of endeavor, Vu teaches; The apparatus of claim 4, wherein the processor is configured to diagnose deformation of an internal structure of the battery by analyzing a change rate of peaks of the pixel value corresponding to each peak position that appears across a diagnosis target section within the plurality of zones (Vu, [0073]-[0074] the internal cathode structures are detected on the cross sectional images, the intensity values are plotted for these images, [0075]-[0076] the plotted values are used in diagnosing the battery based on changes in the values over the plots, where the plots shown in figure 8D and 9D show the peaks in the pixel values being used to diagnose the battery on the plot, [0071] the analysis of the internal battery images are used to diagnose internal structure defects within the battery).
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(Vu, Figure 8D)
The combination of Kim, Wegner, Cha and Vu would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The motivation for the combination lies in that the addition of the peak plot assessment method of Vu to diagnose internal battery defects would improve the system by allowing a faster and more reliable defect detection using image data from images (Vu, [0001]-[0010]).
Regarding claim 6 the combination of Kim, Wegner, Cha and Vu teaches; The apparatus of claim 5, wherein the processor is configured to determine that the deformation of the internal structure of the battery has occurred at a peak position corresponding to an outlier change rate among a plurality of change rates for each peak position (Cha, [0106] the system may use rule based defect region methods, where the pixels for an area are extracted, the average brightness/intensity for that region is taken and then the pixel whose value is most different from the average range is used to determine the region of the defect, where the examiner is interpreting this an outlier in the intensity values).
The combination of Kim, Wegner, Cha and Vu would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Regarding claim 13 the combination of Kim, Wegner, Cha and Vu teaches; The method of claim 12, wherein, in the diagnosing of the battery, the processor is configured to diagnose deformation of an internal structure of the battery by analyzing a change rate of peaks of the pixel value corresponding to each peak position that appears across a diagnosis target section within the plurality of zones (Vu, [0073]-[0074] the internal cathode structures are detected on the cross sectional images, the intensity values are plotted for these images, [0075]-[0076] the plotted values are used in diagnosing the battery based on changes in the values over the plots, where the plots shown in figure 8D and 9D show the peaks in the pixel values being used to diagnose the battery on the plot, [0071] the analysis of the internal battery images are used to diagnose internal structure defects within the battery).
The combination of Kim, Wegner, Cha and Vu would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The motivation for the combination lies in that the addition of the peak plot assessment method of Vu to diagnose internal battery defects would improve the system by allowing a faster and more reliable defect detection using image data from images (Vu, [0001]-[0010]).
Regarding claim 14 the combination of Kim, Wegner, Cha and Vu teaches; The method of claim 13, wherein, in the diagnosing of the battery, the processor is configured to determine that the deformation of the internal structure of the battery has occurred at a peak position corresponding to an outlier change rate among a plurality of change rates for each peak position (Cha, [0106] the system may use rule based defect region methods, where the pixels for an area are extracted, the average brightness/intensity for that region is taken and then the pixel whose value is most different from the average range is used to determine the region of the defect, where the examiner is interpreting this an outlier in the intensity values).
The combination of Kim, Wegner, Cha and Vu would be obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The combination of Kim and Wegner teaches a method where a battery is imaged to create a 3D image of the battery with battery cross sections, where the cross sections are analyzed for defects by area. The motivation to add the peak pixel detection method of Cha to this is that pixel peak based feature or defect detection allows for faster, rule based or value-based detection and classification of the defect in the image. (Cha, [0002]-[0011])
Claims 7 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Kim (US 20260011796 A1) in view of Wegner (US 20240097215 A1) and in further view of Cha (US 20250371696 A1) and Vu (US 20230237634 A1) and in view of Jiang (US 20240005469 A1).
Regarding claim 7 the combination of Kim, Wegner, Cha and Vu fails to teach; The apparatus of claim 5, wherein the diagnosis target section is a section excluding a saturation section in which the change rate of the peaks of the pixel value corresponding to each peak position is saturated from the plurality of zones.
However in the same field of defect inspection, Jiang teaches; wherein the diagnosis target section is a section excluding a saturation section in which the change rate of the peaks of the pixel value corresponding to each peak position is saturated from the plurality of zones (Jiang, [0052] the system determines a defect diagnosis by determining a maximum pixel value in an image (saturation section, where a saturated pixel is a pixel at max value), [0110] where the determined maximum value anomaly section (saturation section) is excluded from the image and the image may be diagnosed).
The combination of Kim, Wegner, Cha, Vu, and Jiang would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The motivation for the addition of the pixel exclusion method of Jiang is that it would improve the speed of the processing method by reducing the amount of data needed to process. (Jiang, [0005]-[0010])
Regarding claim 15 the combination of Kim, Wegner, Cha, Vu, and Jiang teaches; The method of claim 13, wherein the diagnosis target section is a section excluding a saturation section in which the change rate of the peaks of the pixel value corresponding to each peak position is saturated from the plurality of zones (Jiang, [0052] the system determines a defect diagnosis by determining a maximum pixel value in an image (saturation section, where a saturated pixel is a pixel at max value), [0110] where the determined maximum value anomaly section (saturation section) is excluded from the image and the image may be diagnosed).
The combination of Kim, Wegner, Cha, Vu, and Jiang would have been obvious to one of ordinary skill in the art prior to the effective filing date of the presently claimed invention. The motivation for the addition of the pixel exclusion method of Jiang is that it would improve the speed of the processing method by reducing the amount of data needed to process. (Jiang, [0005]-[0010])
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. For a listing of relevant prior art as determined by the examiner, please see the attached PTO-892 Notice of References cited form.
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/J.M.E./Examiner, Art Unit 2666
/EMILY C TERRELL/Supervisory Patent Examiner, Art Unit 2666
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