DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
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.
Claim(s) 1-5, 7-9, 11-15, 17-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gonen (U.S. PG-PUB NO. 2024/0387141) in view of Rossek (U.S. PG-PUB NO. 2024/0047174) and further in view of Friedrich (EP 4075126).
-Regarding claim 1, Gonen discloses an image analysis method performed in a surveillance apparatus comprising an image receiver (camera assembly 130, FIG. 1) and an operation processor (control system 135, FIG. 1), the image analysis method comprising: the operation processor controlling the image receiver to receive a plurality of image frames, wherein the plurality of image frames comprises a first image frame and at least one second image frame (plurality of frames, paragraph 79), each of the first image frame and the at least one second image frame comprises a first feature block (one or more target crystals in the initial image, paragraph 88), and a definition of the first feature block of the first image frame (the diffraction score may represent a resolution of the specimen that was captured in terms of Angstroms, paragraph 91); and the operation processor determines the first feature block of the first image frame meets a preset condition (the completeness parameter may be compared to a threshold (e.g., 65%, 70%, or 75%) to determine whether sufficient diffraction data is present, paragraph 82, 85).
Gonen is silent to teaching that different from a definition of the first feature block of the at least one second image frame. However, the claimed limitation is well known in the art as evidenced by Rossek.
In the same field of endeavor, Rossek teaches different from a definition of the first feature block of the at least one second image frame (Kikuchi images obtained at different positions of the active surface 53, interpolating sup-pixel intensity distributions or calculating super-resolution Kikuchi images based on Kikuchi images obtained from slightly different perspectives, paragraph 65).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Gonen with the teaching of Rossek in order to provide more accurate the determination of the material properties.
The combination is silent to teaching that the operation processor taking the first feature block of the first image frame and the first feature block of the at least one second image frame as training samples for training an image analysis model. However, the claimed limitation is well known in the art as evidenced by Friedrich.
In the same field of endeavor, Friedrich teaches the operation processor taking the first feature block of the first image frame and the first feature block of the at least one second image frame as training samples for training an image analysis model (training samples, paragraph 131-132).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination with the teaching of Friedrich in order to reduce the influence of noise and to accurately estimate the actual wave amplitude from sparse intensity patterns.
-Regarding claim 2, the combination further discloses the first image frame and the at least one second image frame are generated by capturing a same object at different time points, or by different image capturing apparatuses (Gonen, paragraph 78-79).
-Regarding claim 3, the combination further discloses the preset condition is that the definition of the first feature block of the first image frame is greater than a preset threshold (Gonen, paragraph 82-85).
-Regarding claim 4, the combination further discloses the definition of the first feature block of the first image frame is greater than the definition of the first feature block of the at least one second image frame (Gonen, intensity value, paragraph 91).
-Regarding claim 5, the combination further discloses the operation processor controlling the image receiver to receive a third image frame comprising a second feature block and further utilizing the image analysis model for analyzing the second feature block to generate an image prediction result (Gonen, paragraph 79; Friedrich, paragraph 107).
-Regarding claim 7, the combination further discloses the image prediction result refers to generation of a third feature block based on the second feature block, and a definition of the third feature block is greater than a definition of the second feature block (Rossek, paragraph 65).
-Regarding claim 8, the combination further discloses a resolution of the first image frame, a resolution of the at least one second image frame and a resolution of the third image frame are identical to one another (Gonen, paragraph 56).
-Regarding claim 9, the combination further discloses the operation processor taking the first feature block of the first image frame and the first feature block of the at least one second image frame as the training samples for training the image analysis model when the operation processor determines the first feature block of the first image frame meets the preset condition, comprising: the operation processor performing image processing on the first feature block of the first image frame according to at least one image information of the first feature block of the at least one second image frame, wherein the at least one image information of the first feature block of the at least one second image frame comprises a viewing angle information, an image size information and/or an image distortion information of the first feature block of the at least one second image frame; and the operation processor taking the processed first feature block of the first image frame and the first feature block of the at least one second feature block as the training samples for training the image analysis model (Rossek, calculating super-resolution Kikuchi images based on Kikuchi images obtained from slightly different perspectives, paragraph 65).
-Regarding claim 11, Gonen discloses a surveillance apparatus comprising: an image receiver (camera assembly 130, FIG. 1); and an operation processor electrically connected to the image receiver (control system 135, FIG. 1); wherein the operation processor is configured to control the image receiver to obtain a plurality of image frames (plurality of frames, paragraph 79) and when the operation processor determines the first feature block of the first image frame meets a preset condition (the completeness parameter may be compared to a threshold (e.g., 65%, 70%, or 75%) to determine whether sufficient diffraction data is present, paragraph 82, 85); wherein the plurality of image frames comprises a first image frame and at least one second image frame (plurality of frames, paragraph 79), each of the first image frame and the at least one second image frame comprises a first feature block (one or more target crystals in the initial image, paragraph 88), and a definition of the first feature block of the first image frame (the diffraction score may represent a resolution of the specimen that was captured in terms of Angstroms, paragraph 91).
Gonen is silent to teaching that different from a definition of the first feature block of the at least one second image frame. However, the claimed limitation is well known in the art as evidenced by Rossek.
In the same field of endeavor, Rossek teaches different from a definition of the first feature block of the at least one second image frame (Kikuchi images obtained at different positions of the active surface 53, interpolating sup-pixel intensity distributions or calculating super-resolution Kikuchi images based on Kikuchi images obtained from slightly different perspectives, paragraph 65).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of Gonen with the teaching of Rossek in order to provide more accurate the determination of the material properties.
The combination is silent to teaching that the operation processor taking the first feature block of the first image frame and the first feature block of the at least one second image frame as training samples for training an image analysis model. However, the claimed limitation is well known in the art as evidenced by Friedrich.
In the same field of endeavor, Friedrich teaches the operation processor taking the first feature block of the first image frame and the first feature block of the at least one second image frame as training samples for training an image analysis model (training samples, paragraph 131-132).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination with the teaching of Friedrich in order to reduce the influence of noise and to accurately estimate the actual wave amplitude from sparse intensity patterns.
-Regarding claim 12, the combination further discloses the first image frame and the at least one second image frame are obtained from an object at different time points, or by different image capturing apparatuses (Gonen, paragraph 78-79).
-Regarding claim 13, the combination further discloses the preset condition is that the definition of the first feature block of the first image frame is greater than a preset threshold (Gonen, paragraph 82-85).
-Regarding claim 14, the combination further discloses the definition of the first feature block of the first image frame is greater than the definition of the first feature block of the at least one second image frame (Gonen, intensity value, paragraph 91).
-Regarding claim 15, the combination further discloses the operation processor is further configured to control the image receiver to obtain a third image frame comprising a second feature block and further utilize the image analysis model for analyzing the second feature block to generate an image prediction result (Gonen, paragraph 79; Friedrich, paragraph 107).
-Regarding claim 17, the combination further discloses the image prediction result refers to generating a third feature block based on the second feature block, and a definition of the third feature block is greater than a definition of the second feature block (Rossek, paragraph 65).
-Regarding claim 18, the combination further discloses a resolution of the first image frame, a resolution of the at least one second image frame and a resolution of the third image frame are identical to one another (Gonen, paragraph 56).
-Regarding claim 19, the combination further discloses the operation processor is further configured to perform image processing on the first feature block of the first image frame according to at least one image information of the first feature block of the at least one second image frame and use the processed first feature block of the first image frame and the first feature block of the at least one second feature block as the training samples for training the image analysis model, the at least one image information of the first feature block of the at least one second image frame comprises a viewing angle information, an image size information and/or an image distortion information of the first feature block of the at least one second image frame (Rossek, calculating super-resolution Kikuchi images based on Kikuchi images obtained from slightly different perspectives, paragraph 65).
Claim(s) 6 and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gonen (U.S. PG-PUB NO. 2024/0387141) in view of Rossek (U.S. PG-PUB NO. 2024/0047174), Friedrich (EP 4075126) and further in view of Trimby (U.S. PG-PUB NO. 2023/0395350).
-Regarding claim 6, the combination is silent to teaching that the image prediction result is a text recognition result, a number recognition result or a symbol recognition result.. However, the claimed limitation is well known in the art as evidenced by Trimby.
In the same field of endeavor, Trimby teaches the image prediction result is a text recognition result, a number recognition result or a symbol recognition result (paragraph 89).
Therefore, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to combine the teaching of the combination with the teaching of Trimby in order to provide geometric calibration parameters which are precisely relevant to the current location can therefore be used in the simulation of the template.
-Regarding claim 16, the combination further discloses the image prediction result refers to a text recognition result, a number recognition result or a symbol recognition result (Trimby, paragraph 89).
Allowable Subject Matter
Claims 10 and 20 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PING Y HSIEH whose telephone number is (571)270-3011. The examiner can normally be reached Monday-Friday, 9am-4pm.
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/PING Y HSIEH/ Primary Examiner, Art Unit 2664
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