DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “image receiver” in claims 1 and 13.
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.
Regarding claims 1 and 13, “image receiver” be interpreted under 35 U.S.C. 112(f) as a generic image sensor (e.g. a camera) or similar device as described in ¶0022 of the specification.
Claims 2-12 and 14-20 are interpreted similarly due to their dependencies.
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
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.
Claims 1-20 are 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.
Regarding claims 1-7, 9, 13-18 and 20, the phrase "adapted to" renders the claim indefinite because it is unclear whether the limitation(s) following the phrase are part of the claimed invention. See MPEP § 2173.05(d). The Examiner will interpret “adapted to” to mean that the subject of the limitation to directly perform the task. For example, in claim 1, “the operation processor is further adapted to divide a base image” will be interpreted as “the operation processor further divides a base image”. Other occurrences of the phrase will be interpreted similarly.
Claims 8, 10-12, and 9 are rejected due to their dependencies.
Regarding claims 4 and 16, the phrase "the plurality of first auxiliary images" renders the claim indefinite because it is unclear the phrase can have multiple meanings. In claims 4 and 16, “the plurality of first auxiliary images” refers to images acquired by dividing the analysis image. However, in claims 1 and 13, “the plurality of first auxiliary images” refers to images acquired by dividing the original reference image. The Examiner will interpret the “the plurality of first auxiliary images” in claims 4 and 16 to mean “the plurality of auxiliary images acquired from dividing the analysis image”.
Regarding claims 4 and 16, the term “changed” in is a relative term which renders the claim indefinite. The term “changed” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “changed” does not define what constitutes a change, for example whether the classification output of a specific input or the accuracy of the model as a whole, nor which results are being compared. The Examiner will interpret change to indicate a difference in individual output or model accuracy and the comparison to be between “the plurality of auxiliary images acquired from dividing the analysis image” and “the plurality of auxiliary images acquired from dividing the original reference image”.
Regarding claims 6, the term “changed” in is a relative term which renders the claim indefinite. The term “changed” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “changed” does not define which results are being compared. The Examiner will interpret change to indicate a difference in individual output or model accuracy and the comparison to be between “the plurality of auxiliary images spaced from each other” and “the plurality of auxiliary images not spaced from each other”.
Regarding claims 8 and 19, the phrase " the plurality of second auxiliary images" renders the claim indefinite because it is unclear the phrase can have multiple meanings. In claims 8 and 19, “the plurality of first auxiliary images” refers to images acquired by dividing the original image. However, in claims 1 and 13, “the plurality of second auxiliary images” refers to images acquired by dividing the base image. The Examiner will interpret the “the plurality of second auxiliary images” in claims 8 and 19 to mean “the plurality of auxiliary images acquired from dividing the base image”.
Regarding claims 8 and 19, the term “changed” in is a relative term which renders the claim indefinite. The term “changed” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. The term “changed” does not define what constitutes a change, for example whether the classification results of a specific input or the accuracy of the model as a whole, nor which results are being compared. The Examiner will interpret change to indicate a difference in individual output or model accuracy and the comparison to be between “the plurality of auxiliary images acquired from dividing the original image” and “the plurality of auxiliary images acquired from dividing the base image”.
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 and 13 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1 and 13, with Claim 1 being exemplary, recite:
“(a) the image analysis apparatus having an operation processor and (b) an image receiver, (c) the image receiver being adapted to acquire an original image relevant to a surveillance environment, the image analysis method comprising: (d) the operation processor setting a range provided by the original image as a reference image; and (e) the operation processor dividing the reference image into a plurality of first auxiliary images in accordance with a valid size, (f) so as to apply the plurality of first auxiliary images for an image analysis model to generate an image classification result; (g) wherein the operation processor is further adapted to divide a base image acquired by the image receiver into a plurality of second auxiliary images in accordance with the valid size, and (h) apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of first auxiliary images” [Emphasis added]
According to the USPTO guidelines, a claim is directed to non-statutory subject matter if:
STEP 1: the claim does not fall within one of the four statutory categories of invention (process, machine, manufacture or composition of matter), or
STEP 2: the claim recites a judicial exception, e.g. an abstract idea, without reciting additional elements that amount to significantly more than the judicial exception, as determined using the following analysis:
STEP 2A (PRONG 1): Does the claim recite an abstract idea, law of nature, or natural phenomenon?
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application?
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
Using the two-step inquiry, it is clear that the independent claim 1 is directed to an abstract idea as shown below:
STEP 1: Do the claims fall within one of the statutory categories? YES. Independent claims 1 and 13 are directed to a method and an apparatus, respectively.
STEP 2A (PRONG 1): Is the claim directed to a law of nature, a natural phenomenon, or an abstract idea? YES. Independent claims 1 and 13 are directed towards a mental process (i.e. an abstract idea).
Regarding claims 1 and 13, limitations (d)-(h), in emphasized claims 1 and 13 above, are mental processes. Limitation (d) is a mental process as the human mind could determine a region of interest in an image, such as a person or object in the image, and set that region as the area to be analyzed. Limitations (e) and (g) are mental processes as the human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image. Limitation (f) is a mental process because the human mind is capable of generating a classification result, such as whether a person in an image is looking left or right. Limitation (h) is a mental process because the human mind can determine how many patches to divide an image into based on, for example, whether the patches would be large enough to contain objects of interest.
STEP 2A (PRONG 2): Does the claim recite additional elements that integrate the judicial exception into a practical application? NO. Independent claims 1 and 13 do not recite additional elements that integrate the judicial exception into a practical application.
Regarding claims 1 and 13, limitations (a) and (b), in emphasized claims 1 and 13 above, are mere generic computer elements, a processor and a sensor, and thus amount to no more than a recitation of the words "apply it" (or an equivalent) or are no more than mere instructions to implement an abstract idea or other exception on a computer (see MPEP §2106.05(f)). Limitation (c) is an additional element, receiving an image, that falls under insignificant extra-solution activity since it is merely data gathering and data output (see MPEP §2106.05(g)).
STEP 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception? NO. Independent claims 1 and 13 do not recite additional elements that amount to significantly more than the judicial exception.
Regarding claims 1 and 13, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because when considered separately and in combination, the above recited additional elements from claim 1 do not add significantly more (also known as an “inventive concept”) to the exception. Rather, the additional elements disclosed above perform well-understood, routine, conventional computer functions as recognized by the court decisions listed in MPEP §2106.05(d).
Therefore, independent claims 1 and 13 are directed towards an abstract idea without a practical application or significantly more.
Regarding claims 2 and 14, with claim 2 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitation: “wherein the operation processor is adapted to directly define the range within the original image to set as the reference image” falls under a mental process as a human mind could determine a region of interest, for example areas including people (see MPEP §2106.04(a)(2)(III)).
Regarding claims 3 and 15, with claim 3 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitation: “wherein the operation processor is adapted to reduce the original image into an analysis image, and define the range within the analysis image to set as the reference image” falls under selecting a data type (see MPEP §2106.05(g)).
Regarding claims 4 and 16, with claim 4 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the operation processor is adapted to divide the reference image defined by the range within the analysis image into the plurality of first auxiliary images, and the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model” fall under a mental process as a human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image, and classifying an image, such as determining whether a person is in the image (see MPEP §2106.04(a)(2)(III)).
Regarding claims 5 and 17, with claim 5 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the operation processor is adapted to utilize the valid size to divide the reference image into the plurality of first auxiliary images partly overlapped with each other, or utilize the valid size to divide the reference image into the plurality of first auxiliary images spaced from each other” fall under a mental process as a human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image (see MPEP §2106.04(a)(2)(III)).
Regarding claim 6, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the operation processor is adapted to divide the reference image into the plurality of first auxiliary images spaced from each other, and the image classification result is not changed when the plurality of first auxiliary images is applied for the image analysis model” fall under a mental process as a human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image, and classifying an image, such as determining whether a person is in the image (see MPEP §2106.04(a)(2)(III)).
Regarding claims 7 and 18, with claim 7 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the operation processor is adapted to apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of second auxiliary images, and decide optimal solution of the valid size, and then divide the reference image via the decided valid size to decide the plurality of first auxiliary images, so that the number of the plurality of first auxiliary images is the same as the number of the plurality of second auxiliary images” fall under a mental process as the human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image, and determine how many patches to divide an image into based on, for example, whether the patches would be large enough to contain objects of interest (see MPEP §2106.04(a)(2)(III)).
Regarding claims 8 and 19, with claim 8 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the original image divided into the plurality of second auxiliary images is applied for the image analysis model to acquire the image classification result, and the reference image divided into the plurality of first auxiliary images is applied for the image analysis model to change the image classification result” fall under a mental process as a human mind is capable of dividing an image into smaller parts, such as by imposing a grid over the image, and classifying an image, such as determining whether a person is in the image (see MPEP §2106.04(a)(2)(III)).
Regarding claims 9 and 20, with claim 9 being exemplary, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitation: “wherein the operation processor is adapted to reduce the original image via a first preset ratio for generating the analysis image, and partly overlap two adjacent first auxiliary images of the plurality of first auxiliary images via a second preset ratio, a sum of the first preset ratio and the second preset ratio is greater than or equal to 1” fall under selecting a data type (see MPEP §2106.05(g)).
Regarding claim 10, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitation: “wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor utilizing a preset ratio to change a vertical size and a horizontal size of the original image to generate the analysis image” falls under selecting a data type (see MPEP §2106.05(g)).
Regarding claim 11, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitations: “wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor computing a preset percentage of a pixel number difference between the original image and the analysis image in a horizontal direction, so as to define an interval between a vertical boundary of the analysis image and a related vertical boundary of the original image; and the operation processor computing the preset percentage of a pixel number difference between the original image and the analysis image in a vertical direction, so as to define an interval between a horizontal boundary of the analysis image and a related horizontal boundary of the original image” fall under a mental process as a human as the human mind could calculate the percentage of pixels and determine an interval (see MPEP §2106.04(a)(2)(III)).
Regarding claim 12, the additional limitations do not integrate the abstract idea into a practical application or add significantly more to the abstract idea. The limitation: “wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor utilize a foreground detection technology to set a region of interest within the original image; and the operation processor setting a coverage range of the analysis image within the original image based on a center of the region of interest” falls under fall under a mental process as a human as the human mind could determine a foreground, for example by selecting areas with people, and determine the center of the region of interest (see MPEP §2106.04(a)(2)(III)).
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, 2, 5, 7, 8, 13, 14, and 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Jönsson et al. (US 2022/0114736) (hereafter, “Jönsson”) in view of Lee et al. (US 2023/0298351) (hereafter, “Lee”).
Regarding claim 1, Jönsson discloses an image analysis method applied to an image analysis apparatus, the image analysis apparatus having an operation processor (¶0069, central processing unit 304) and an image receiver (¶0069, a camera 301), the image receiver being adapted to acquire an original image (¶0034, acquiring a sequence of image frames from a camera) relevant to a surveillance environment (¶0026, run as a part of a surveillance system), the image analysis method comprising: the operation processor setting a range provided by the original image (¶0046, a predefined region such as a region of interest. Examiner considers the predefined region as a “range”) [as a reference image]; and the operation processor dividing the [reference] image into a plurality of first auxiliary images in accordance with a valid size (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks; ¶0046, set with a smaller block size. Examiner considers the block size as the “valid size”. Examiner notes that Jönsson discloses dividing an image, which can be applied to the reference image taught by Lee), so as to apply the plurality of first auxiliary images for an image analysis model to generate an image classification result (¶0036, For image blocks having a measure of dissimilarity less than a threshold it may be assumed that there is no or limited movement. … For image blocks having a measure of dissimilarity greater than the threshold it can be assumed that there is movement within the image block. ¶0052, The presently disclosed motion segmentation may produce a motion mask. Examiner considers the measure of dissimilarity as the “analysis model” and the motion mask as the “classification result”); wherein the operation processor is further adapted to divide a base image acquired by the image receiver into a plurality of second auxiliary images in accordance with the valid size (¶0036, the second image frame also is divided into corresponding reference image blocks. Examiner considers the second image as the “base image”), and apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of first auxiliary images (¶0036, the image blocks and reference image blocks are compared one by one; ¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration).
However, Jönsson fails to explicitly disclose a reference image acquired by setting the range.
Lee teaches a reference image acquired by setting the range (¶0115, zoom into all the regions of interest and pass the cropped image).
Both Jönsson and Lee are analogous to the claimed invention because both are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the region of interest cropping of Lee into image division of Jönsson. The suggestion/motivation for doing so would have been to use more details in image analysis, as suggested by Lee at ¶0115, This approach allows the use of more of the data of the object of interest to “zoom” into details such as the writing on a product label.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee to obtain the invention as specified in claim 1.
Regarding claim 2, in which claim 1 is incorporated, Jönsson discloses wherein the operation processor is adapted to directly define the range within the original image (¶0070, The system (300) further comprises a processing unit (303) in the form of a central processing unit (CPU) configured to perform the presently disclosed method of motion segmentation (305) on raw image data from the image sensor (302). The motion segmentation (305) provides a region of interest) [to set as the reference image].
However, Jönsson fails to explicitly disclose a reference image acquired by setting the range.
Lee teaches a reference image acquired by setting the range (¶0115, zoom into all the regions of interest and pass the cropped image).
Both Jönsson and Lee are analogous to the claimed invention because both are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the region of interest cropping of Lee into image division of Jönsson. The suggestion/motivation for doing so would have been to use more details in image analysis, as suggested by Lee at ¶0115, This approach allows the use of more of the data of the object of interest to “zoom” into details such as the writing on a product label.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee to obtain the invention as specified in claim 2.
Regarding claim 5, in which claim 1 is incorporated, Jönsson discloses wherein the operation processor is adapted to utilize the valid size to divide the reference image into the plurality of first auxiliary images partly overlapped with each other, or utilize the valid size to divide the reference image into the plurality of first auxiliary images spaced from each other (¶0046, having gaps between the image blocks is not excluded as an option for the presently disclosed method of motion segmentation. Since the limitation is recited in the alternative, Examiner considers this citation to fully disclose the limitation).
Regarding claim 7, in which claim 1 is incorporated, Jönsson discloses wherein the operation processor is adapted to apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of second auxiliary images (¶0049, compute or extract an average pixel value for the image block being compared and compare against the average pixel value of the corresponding reference image block. ¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration. Comparing blocks 1 to 1 implies the same number of blocks. Therefore, the block number determining step applies to both the first and second auxiliary images), and decide optimal solution of the valid size (¶0054, An alternative way of controlling the number of image blocks for further division is to adjust the threshold. In one embodiment the threshold is adjusted after each iteration based on the measure of dissimilarity for the pairs of image blocks. Examiner considers iteratively adjusting a threshold to be an optimization routine), and then divide the reference image via the decided valid size to decide the plurality of first auxiliary images (¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration), so that the number of the plurality of first auxiliary images is the same as the number of the plurality of second auxiliary images (¶0049, compute or extract an average pixel value for the image block being compared and compare against the average pixel value of the corresponding reference image block. Comparing blocks 1 to 1 implies the same number of blocks).
Regarding claim 8, in which claim 1 is incorporated, Jönsson discloses wherein the original image divided into the plurality of second auxiliary images is applied for the image analysis model to acquire the image classification result (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks; ¶0052, The presently disclosed motion segmentation may produce a motion mask showing which areas that contain motion and which do not contain motion), and the reference image divided into the plurality of first auxiliary images is applied for the image analysis model to change the image classification result (¶0055, As an example, a central region of the image may be more important for the motion mask than peripheral regions. These areas may then be associated with a higher (or lower) priority than other areas… step c) is only performed for a selected number of image blocks, wherein the image blocks are prioritized. Examiner considers this to imply a motion mask without masking motion in peripheral regions, which differs from a mask derived from the entire image).
Regarding claim 13, Jönsson discloses an image analysis apparatus, comprising: an image receiver adapted to acquire an original image (¶0034, acquiring a sequence of image frames from a camera); and an operation processor electrically connected with the image receiver (CPU (304) is configured to … control settings of the image sensor (302) and/or camera (301)), and adapted to set a range provided by the original image (¶0046, a predefined region such as a region of interest. Examiner considers the predefined region as a “range”) [as a reference image], and divide the [reference] image into a plurality of first auxiliary images in accordance with a valid size (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks; ¶0046, set with a smaller block size. Examiner considers the block size as the “valid size”. Examiner notes that Jönsson discloses dividing an image, which can be applied to the reference image taught by Lee), so as to apply the plurality of first auxiliary images for an image analysis model to generate an image classification result (¶0036, For image blocks having a measure of dissimilarity less than a threshold it may be assumed that there is no or limited movement. … For image blocks having a measure of dissimilarity greater than the threshold it can be assumed that there is movement within the image block. ¶0052, The presently disclosed motion segmentation may produce a motion mask. Examiner considers the measure of dissimilarity as the “analysis model” and the motion mask as the “classification result”); wherein the operation processor is further adapted to divide a base image acquired by the image receiver into a plurality of second auxiliary images in accordance with the valid size (¶0036, the second image frame also is divided into corresponding reference image blocks. Examiner considers the second image as the “base image”), and apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of first auxiliary images (¶0036, the image blocks and reference image blocks are compared one by one; ¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration).
However, Jönsson fails to explicitly disclose a reference image acquired by setting the range.
Lee teaches a reference image acquired by setting the range (¶0115, zoom into all the regions of interest and pass the cropped image).
Both Jönsson and Lee are analogous to the claimed invention because both are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the region of interest cropping of Lee into image division of Jönsson. The suggestion/motivation for doing so would have been to use more details in image analysis, as suggested by Lee at ¶0115, This approach allows the use of more of the data of the object of interest to “zoom” into details such as the writing on a product label.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee to obtain the invention as specified in claim 13.
Regarding claim 14, in which claim 13 is incorporated, Jönsson discloses wherein the operation processor is adapted to directly define the range within the original image (¶0070, The system (300) further comprises a processing unit (303) in the form of a central processing unit (CPU) configured to perform the presently disclosed method of motion segmentation (305) on raw image data from the image sensor (302). The motion segmentation (305) provides a region of interest) [to set as the reference image].
However, Jönsson fails to explicitly disclose a reference image acquired by setting the range.
Lee teaches a reference image acquired by setting the range (¶0115, zoom into all the regions of interest and pass the cropped image).
Both Jönsson and Lee are analogous to the claimed invention because both are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the region of interest cropping of Lee into image division of Jönsson. The suggestion/motivation for doing so would have been to use more details in image analysis, as suggested by Lee at ¶0115, This approach allows the use of more of the data of the object of interest to “zoom” into details such as the writing on a product label.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee to obtain the invention as specified in claim 14.
Regarding claim 17, in which claim 13 is incorporated, Jönsson discloses wherein the operation processor is adapted to utilize the valid size to divide the reference image into the plurality of first auxiliary images partly overlapped with each other, or utilize the valid size to divide the reference image into the plurality of first auxiliary images spaced from each other(¶0046, having gaps between the image blocks is not excluded as an option for the presently disclosed method of motion segmentation. Since the limitation is recited in the alternative, Examiner considers this citation to fully disclose the limitation).
Regarding claim 18, in which claim 13 is incorporated, Jönsson discloses wherein the operation processor is adapted to apply the plurality of second auxiliary images for the image analysis model to decide a number of the plurality of second auxiliary images (¶0049, compute or extract an average pixel value for the image block being compared and compare against the average pixel value of the corresponding reference image block. ¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration. Comparing blocks 1 to 1 implies the same number of blocks. Therefore, the block number determining step applies to both the first and second auxiliary images), and decide optimal solution of the valid size (¶0054, An alternative way of controlling the number of image blocks for further division is to adjust the threshold. In one embodiment the threshold is adjusted after each iteration based on the measure of dissimilarity for the pairs of image blocks. Examiner considers iteratively adjusting a threshold to be an optimization routine), and then divide the reference image via the decided valid size to decide the plurality of first auxiliary images (¶0054, the image blocks can then be prioritized such that the image blocks having the greatest measure of dissimilarity are selected for further division and iteration), so that the number of the plurality of first auxiliary images is the same as the number of the plurality of second auxiliary images (¶0049, compute or extract an average pixel value for the image block being compared and compare against the average pixel value of the corresponding reference image block. Comparing blocks 1 to 1 implies the same number of blocks).
Regarding claim 19, in which claim 13 is incorporated, Jönsson discloses wherein the original image divided into the plurality of second auxiliary images is applied for the image analysis model to acquire the image classification result (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks; ¶0052, The presently disclosed motion segmentation may produce a motion mask showing which areas that contain motion and which do not contain motion), and the reference image divided into the plurality of first auxiliary images is applied for the image analysis model to change the image classification result (¶0055, As an example, a central region of the image may be more important for the motion mask than peripheral regions. These areas may then be associated with a higher (or lower) priority than other areas… step c) is only performed for a selected number of image blocks, wherein the image blocks are prioritized. Examiner considers this to imply a motion mask without masking motion in peripheral regions, which differs from a mask derived from the entire image).
Claims 3, 4, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Jönsson et al. (US 2022/0114736) (hereafter, “Jönsson”) in view of Lee et al. (US 2023/0298351) (hereafter, “Lee”) as applied to claims 1 and 13 above, and further in view of Bakhshmand (US 2026/0105590).
Regarding claim 3, in which claim 1 is incorporated, Jönsson discloses [wherein the operation processor is adapted to reduce the original image into an analysis image], and define the range within the analysis image to set as the reference image (¶0070, The system (300) further comprises a processing unit (303) in the form of a central processing unit (CPU) configured to perform the presently disclosed method of motion segmentation (305) on raw image data from the image sensor (302). The motion segmentation (305) provides a region of interest).
However, neither Jönsson nor Lee, whether considered individually or in combination, disclose wherein the operation processor is adapted to reduce the original image into an analysis image.
Bakhshmand teaches wherein the operation processor is adapted to reduce the original image into an analysis image (¶0221, cropping size is equal to the input size of the classifier model 352, and cropped image 350a is generated. Examiner considers cropping an image to the input size as “reducing” the image).
Jönsson, Lee, and Bakhshmand are analogous to the claimed invention because all three are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the image reduction of nto Bakhshmand into the region of interest cropping of Lee and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve accuracy, as suggested by Bakhshmand at ¶0223, classification accuracy may be improved.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee and Bakhshmand.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee and Bakhshmand to obtain the invention as specified in claim 3.
Regarding claim 4, in which claim 3 is incorporated, Jönsson discloses wherein the operation processor is adapted to divide the reference image defined by the range within the analysis image into the plurality of first auxiliary images (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks), and [the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model].
However, neither Jönsson nor Lee, whether considered individually or in combination, disclose the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model.
Bakhshmand teaches the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model (¶0223, adaptive cropping … classification accuracy may be improved. Without adaptive cropping, contextual information such as size and dimension ratio of cropped anomalies may be lost. Examiner considers improving classification accuracy to mean “changing the result”).
Jönsson, Lee, and Bakhshmand are analogous to the claimed invention because all three are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the image reduction of nto Bakhshmand into the region of interest cropping of Lee and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve accuracy, as suggested by Bakhshmand at ¶0223, classification accuracy may be improved.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee and Bakhshmand.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee and Bakhshmand to obtain the invention as specified in claim 4.
Regarding claim 15, in which claim 13 is incorporated, Jönsson discloses [wherein the operation processor is adapted to reduce the original image into an analysis image], and define the range within the analysis image to set as the reference image (¶0070, The system (300) further comprises a processing unit (303) in the form of a central processing unit (CPU) configured to perform the presently disclosed method of motion segmentation (305) on raw image data from the image sensor (302). The motion segmentation (305) provides a region of interest).
However, , neither Jönsson nor Lee, whether considered individually or in combination, disclose wherein the operation processor is adapted to reduce the original image into an analysis image.
Bakhshmand teaches wherein the operation processor is adapted to reduce the original image into an analysis image (¶0221, cropping size is equal to the input size of the classifier model 352, and cropped image 350a is generated. Examiner considers cropping an image to the input size as “reducing” the image).
Jönsson, Lee, and Bakhshmand are analogous to the claimed invention because all three are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the image reduction of nto Bakhshmand into the region of interest cropping of Lee and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve accuracy, as suggested by Bakhshmand at ¶0223, classification accuracy may be improved.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee and Bakhshmand.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee and Bakhshmand to obtain the invention as specified in claim 15.
Regarding claim 16, in which claim 15 is incorporated, Jönsson discloses wherein the operation processor is adapted to divide the reference image defined by the range within the analysis image into the plurality of first auxiliary images (¶0035, dividing a first image frame from the sequence of image frames into a plurality of image blocks), and [the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model].
However, , neither Jönsson nor Lee, whether considered individually or in combination, disclose the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model.
Bakhshmand teaches the image classification result is changed when the plurality of first auxiliary images is applied for the image analysis model (¶0223, adaptive cropping … classification accuracy may be improved. Without adaptive cropping, contextual information such as size and dimension ratio of cropped anomalies may be lost. Examiner considers improving classification accuracy to mean “changing the result”).
Jönsson, Lee, and Bakhshmand are analogous to the claimed invention because all three are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the image reduction of Bakhshmand into the region of interest cropping of Lee and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve accuracy, as suggested by Bakhshmand at ¶0223, classification accuracy may be improved.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee and Bakhshmand.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee and Bakhshmand to obtain the invention as specified in claim 16.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Jönsson et al. (US 2022/0114736) (hereafter, “Jönsson”) in view of Lee et al. (US 2023/0298351) (hereafter, “Lee”) as applied to claim 1 above, and further in view of Motoki (US 2020/0104708).
Regarding claim 6, in which claim 1 is incorporated, Jönsson discloses wherein the operation processor is adapted to divide the reference image into the plurality of first auxiliary images spaced from each other (¶0046, having gaps between the image blocks is not excluded as an option for the presently disclosed method of motion segmentation), and [the image classification result is not changed when the plurality of first auxiliary images is applied for the image analysis model].
However, neither Jönsson nor Lee, whether considered individually or in combination, explicitly disclose the image classification result is not changed when the plurality of first auxiliary images is applied for the image analysis model.
Motoki teaches the image classification result is not changed when the plurality of first auxiliary images is applied for the image analysis model (¶0145, according to the trained model 920 with the autoregression module, the operations can be performed without influence due to a gap arising as a result of dividing the pre-processed image data).
Jönsson, Lee, and Motoki are analogous to the claimed invention because all three are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the gap mitigation of Motoki into the region of interest cropping of Lee and the image division of Jönsson. The suggestion/motivation for doing so would have been to use increased image context, as suggested by Motoki at ¶0116, phenomena at other positions in the same concatenated data can be reflected.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee and Motoki.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee and Motoki to obtain the invention as specified in claim 6.
Claims 9, 10, 12, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Jönsson et al. (US 2022/0114736) (hereafter, “Jönsson”) in view of Lee et al. (US 2023/0298351) (hereafter, “Lee”) and Bakhshmand (US 2026/0105590) as applied to claims 3 and 15 above, and further in view of Steiner et al. (US 2025/0117893) (hereafter, “Steiner”).
Regarding claim 9, Jönsson in view of Lee and Bakhshmand discloses the image analysis method of claim 3.
However, none of Jönsson, Lee, or Bakhshmand, whether considered individually or in combination, explicitly disclose wherein the operation processor is adapted to reduce the original image via a first preset ratio for generating the analysis image, and partly overlap two adjacent first auxiliary images of the plurality of first auxiliary images via a second preset ratio, a sum of the first preset ratio and the second preset ratio is greater than or equal to 1.
Steiner teaches wherein the operation processor is adapted to reduce the original image via a first preset ratio for generating the analysis image (¶0076, A 1:1 patch 202 can be extracted at a native resolution), and partly overlap two adjacent first auxiliary images of the plurality of first auxiliary images via a second preset ratio (Fig. 4, top row; ¶0097, achieve a threshold proportion of overlap), a sum of the first preset ratio and the second preset ratio is greater than or equal to 1 (¶0076, A 1:1 patch. Since the ratio in Steiner is 1, all sums with it must be greater than or equal to 1).
Jönsson, Lee, Bakhshmand, and Steiner are analogous to the claimed invention because all are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the ratios of Steiner into the image reduction of Bakhshmand, the region of interest cropping of Lee, and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve scalability and generalizability, as suggested by Steiner at ¶0055, the present disclosure provides improvements to the scalability and generalizability of machine-learned image processing models.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee, Bakhshmand, and Steiner.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee, Bakhshmand, and Steiner to obtain the invention as specified in claim 9.
Regarding claim 10, Jönsson in view of Lee, Bakhshmand, and Steiner discloses the image analysis method of claim 9.
However, none of Jönsson, Lee, or Bakhshmand, whether considered individually or in combination, explicitly disclose wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor utilizing a preset ratio to change a vertical size and a horizontal size of the original image to generate the analysis image.
Steiner teaches wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor utilizing a preset ratio to change a vertical size and a horizontal size of the original image to generate the analysis image (Fig. 2, #204; ¶0081, to emulate a lower magnification than the native magnification, a portion of the original image having a dimension larger than the input dimension can be resampled/regenerated to form an emulated lower magnification patch 204 that has dimension(s) aligned to the input dimension(s). Examiner considers the magnification to be a “ratio” and that aligning plurality of dimensions indicates both the “vertical” and “horizontal” sizes as illustrated in Fig. 2 #205).
Jönsson, Lee, Bakhshmand, and Steiner are analogous to the claimed invention because all are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the ratios of Steiner into the image reduction of Bakhshmand, the region of interest cropping of Lee, and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve scalability and generalizability, as suggested by Steiner at ¶0055, the present disclosure provides improvements to the scalability and generalizability of machine-learned image processing models.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee, Bakhshmand, and Steiner.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee, Bakhshmand, and Steiner to obtain the invention as specified in claim 10.
Regarding claim 12, in which claim 9 is incorporated, Jönsson discloses wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor utilize a foreground detection technology to set a region of interest within the original image (¶0055, a region of interest may be handled different than a surrounding (background) region. Examiner considers separating the region of interest from the background to imply the ROI is in the foreground); and the operation processor setting a coverage range of the analysis image within the original image based on a center of the region of interest (¶0055, a central region of the image may be more important for the motion mask than peripheral regions. These areas may then be associated with a higher (or lower) priority).
Regarding claim 20, Jönsson in view of Lee and Bakhshmand discloses the image analysis apparatus of claim 15.
However, none of Jönsson, Lee, or Bakhshmand, whether considered individually or in combination, explicitly disclose wherein the operation processor is adapted to reduce the original image via a first preset ratio for generating the analysis image, and partly overlap two adjacent first auxiliary images of the plurality of first auxiliary images via a second preset ratio, a sum of the first preset ratio and the second preset ratio is greater than or equal to 1.
Steiner teaches wherein the operation processor is adapted to reduce the original image via a first preset ratio for generating the analysis image (¶0076, A 1:1 patch 202 can be extracted at a native resolution), and partly overlap two adjacent first auxiliary images of the plurality of first auxiliary images via a second preset ratio (Fig. 4, top row; ¶0097, achieve a threshold proportion of overlap), a sum of the first preset ratio and the second preset ratio is greater than or equal to 1 (¶0076, A 1:1 patch. Since the ratio in Steiner is 1, all sums with it must be greater than or equal to 1).
Jönsson, Lee, Bakhshmand, and Steiner are analogous to the claimed invention because all are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the ratios of Steiner into the image reduction of Bakhshmand, the region of interest cropping of Lee, and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve scalability and generalizability, as suggested by Steiner at ¶0055, the present disclosure provides improvements to the scalability and generalizability of machine-learned image processing models.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee, Bakhshmand, and Steiner.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee, Bakhshmand, and Steiner to obtain the invention as specified in claim 20.
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Jönsson et al. (US 2022/0114736) (hereafter, “Jönsson”) in view of Lee et al. (US 2023/0298351) (hereafter, “Lee”), Bakhshmand (US 2026/0105590), and Steiner et al. (US 2025/0117893) (hereafter, “Steiner”)as applied to claim 9 above, and further in view of Morris et al. (US 2022/0155007) (hereafter, “Morris”).
Regarding claim 11, Jönsson in view of Lee, Bakhshmand, and Steiner discloses the image analysis method of claim 9.
However, none of Jönsson, Lee, Bakhshmand, or Steiner, whether considered individually or in combination, explicitly disclose wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor computing a preset percentage of a pixel number difference between the original image and the analysis image in a horizontal direction, so as to define an interval between a vertical boundary of the analysis image and a related vertical boundary of the original image; and the operation processor computing the preset percentage of a pixel number difference between the original image and the analysis image in a vertical direction, so as to define an interval between a horizontal boundary of the analysis image and a related horizontal boundary of the original image.
Morris teaches wherein the operation processor reducing the original image to generate the analysis image comprises: the operation processor computing a preset percentage of a pixel number difference between the original image and the analysis image in a horizontal direction (¶0044, the dimensions of anchor boundary 182 may be increased by fixed percentage or dimension. In this regard, the width. Examiner considers width as the horizontal direction), so as to define an interval between a vertical boundary of the analysis image and a related vertical boundary of the original image (¶0044, increased by 20%, 40%, 50%, 60%, or greater); and the operation processor computing the preset percentage of a pixel number difference between the original image and the analysis image in a vertical direction (¶0044, the dimensions of anchor boundary 182 may be increased by fixed percentage or dimension. In this regard, … depth. Examiner considers width as the vertical direction), so as to define an interval between a horizontal boundary of the analysis image and a related horizontal boundary of the original image (¶0044, increased by 20%, 40%, 50%, 60%, or greater).
Jönsson, Lee, Bakhshmand, Steiner, and Morris are analogous to the claimed invention because all are in the field of image classification. It would have been obvious to a person of ordinary skill before the effective filing date of the claimed invention to incorporate the horizontal and vertical intervals of Morris into the ratios of Steiner, the image reduction of Bakhshmand, the region of interest cropping of Lee, and the image division of Jönsson. The suggestion/motivation for doing so would have been to improve efficiency, as suggested by Morris at ¶0046, detected while minimizing or reducing the necessary processing power, computer memory, or other computational resources.
This method of improving Jönsson was within the ordinary ability of one of ordinary skill in the art based on the teachings of Lee, Bakhshmand, Steiner, and Morris.
Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date, to modify Jönsson with the teachings of Lee, Bakhshmand, Steiner, and Morris to obtain the invention as specified in claim 11.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Yang et al. (US 2020/0074622) discloses overlapping image patches (¶0027, When image patches are used, one input image or volume can optionally be broken down or segmented into multiple overlapping or non-overlapping sections).
Tandia et al. (US 2020/0410660) discloses a method of determining an optimal tile size (¶0033, FIG. 4 illustrates a flowchart 400 for determining the tile size and overlap for a set of super-high-resolution images).
Narayan et al. (US 2023/0368513) discloses patches with spaces in between and overlapping patches (¶0129, spaces between consecutive patches or overlapping consecutive patches).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIAOMAO DING whose telephone number is (571)272-7237. The examiner can normally be reached Mon-Fri 8:00-4:00.
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/XIAOMAO DING/Examiner, Art Unit 2676
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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