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 .
Response to Arguments
In Applicant’s arguments filed on March 19, 2026, Applicant argues that the examiner’s reliance on Huang as teaching the following limitation from claim 1 is incorrect:
“determine non-utilized match points out of the determined first initial match points by calculating the value of position change for each of the first initial match points between the images of the preprocessed image pair, and identifying the non-utilized match points based on a statistical analysis of the calculated value of position change….”
Regarding this limitation, Applicant argues that Huang discloses calculating the value of position change between adjacent points in the same image frame whereas the present invention calculates the value of position change as “the amount of displacement between the position occupied by a single match point in a first image and the position occupied by the same match point in a second image”.
First of all, claim 1 does not recite that the value of position is calculated as “the amount of displacement between the position occupied by a single match point in a first image and the position occupied by the same match point in a second image”. Applicant is reminded that although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
Secondly, Huang does teach calculating the value of position change based on the position occupied by a single match point in a first image and the position occupied by the same match point in a second image for each of the first initial match points. Fig. 2 of Huang is duplicated below for convenience.
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In Fig. 2, the points labeled P1(x1,y1) and P1’(x1’,y1’) correspond to an initial match point in a first image and the same initial match point in a second image, respectively, as discussed in section III.B of Huang. The line shown interconnecting these points has a slope, k, that is based on the positions of the points and their respective x and y coordinate values, as indicated by equation 3 of Huang. It should be noted that a change in the position of point P1 while position P2 stays the same, or vice versa, will be reflected in a change in the slope k of the line interconnecting the points since the slope is based on the coordinates of the points and their differences. Therefore, calculating the slope k constitutes calculating a “value of position change” for each of the first initial match points between the images of the preprocessed image pair.
The slope is calculated and used in the process represented by the flowchart shown in Fig. 3 of Huang as a value upon which a determination is made as to whether a pair of initial match points is to be discarded, i.e., whether the pair is to be excluded as valid match points (Fig. 3 shows block labeled “feature point matching set, R,S” and the block that follows it labeled “calculate the slope k of the corresponding point pair”). Although Huang also uses the distance ratio, D, corresponding to the ratio of the distances between adjacent points in the same image in making the determination as to whether to discard an initial match point pair, Huang nonetheless uses the value of the slope k for each initial match point pair, which is reflective of a change in the position of points Pi and Pi’ of the corresponding initial match point pairs. Therefore, Huang does teach the above-quoted limitation of determining “non-utilized match points out of the determined first initial match points by calculating the value of position change for each of the first initial match points between the images of the preprocessed image pair…”, as recited in claim 1.
Regarding the portion of the above-quoted limitation of “and identifying the non-utilized match points based on a statistical analysis of the calculated value of position change…”, Huang discloses that the “statistical histogram of K bins” is “based on the slope”, as stated in section III.C., step 4 of Huang. The statistical histogram is used in the statistical process of identifying match points to be discarded, and therefore setting up the histogram bins based on the slope calculation and using the values in the histogram bins to determine which match point pairs should be discarded constitutes identifying the non-utilized match points based on a statistical analysis of the calculated value of position change.
Applicant argues many differences between features of Huang and the present invention, but those features of the present invention are not recited in claim 1. As another example of this, Applicant argues “[i]n contrast, in the present invention, the subject of measurement is ‘each match point’ itself. As claim 1 explicitly recites ‘for each of the first initial match points,’ a unique value of position change is calculated for each individual match point. The value is determined solely by the amount of movement of the point itself, regardless of the existence or arrangement of neighboring points.” However, claim 1 does not recite calculating a unique value of position change for each individual match point determined solely by the amount of movement of the point itself.
Regarding the limitation of claim 1 of “wherein the statistical analysis of the calculated value of position change comprises a combined value of the calculated value of position change”, Applicant argues that this is not taught by Huang. The examiner disagrees. The broadest reasonable interpretation (BRI) for this limitation is that the value of position change is calculated for each pair of the initial match points and that the combination of the calculated values of position change for each pair is considered in determining which pairs are to be excluded. The BRI is based on Figs. 5-6c and paras. [0145]-[0150] of the present disclosure.
This is taught by Huang. The statistical analysis of Huang retains “the matching pair of points in the highest bin” of the statistical histogram. Since the histogram bins are based on the slope, and the slope is a calculated value of position change, and since the process depicted in the flowchart of Fig. 3 is performed for the combination of all of the match point pairs, as indicated by the blocks labeled “i=i+1” and “j=j+1” in the flowchart, the statistical analysis of Huang comprises a combined value of the calculated value of position change.
Claim Interpretation
The claims in this application are given their broadest reasonable interpretation (BRI) using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The BRI of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification.
In the following, some of the terms in the claims have been given BRIs in light of the specification. These BRIs are used for purposes of searching for prior art and examining the claims, but cannot be incorporated into the claims. Should Applicant believe that different interpretations are appropriate, Applicant should point to the portions of the specification that clearly support a different interpretation.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3 and 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over an article entitled “An image Stitching Method for Blades of Wind Turbine Based on Background Removal Preprocessing”, by Li, published in 2020 in 5th International Conference on Communication, Image and Signal Processing (CCISP) (2020, Page(s): 174-178) (hereinafter referred to as “Li”) in view of view of U.S. Publ. Appl. No. 2019/0304077 A1 to Wang et al. (hereinafter referred to as “Wang”) and further in view of an article entitled “An Image Registration Algorithm Based on Slope and Distance Ratio Constraints”, by Huang et al., published in 2019 in IEEE International Conference on Signal, Information and Data Processing (ICSIDP) (Page(s): 1-5) (hereinafter referred to as “Huang”).
Regarding claim 1, Li discloses an image stitching apparatus for inspecting a wind turbine (Abstract: “t[]he damage detection of the wind turbine (WT) blade is an important aspect of its health situation monitoring. In order to catch small damages, it is necessary to stitch the multi segment images of the blade to obtain a high resolution image”), comprising:
at least one processor configured to execute instructions stored on a storage medium to (presumably Li uses some type of processor executing software stored on some type of storage medium to perform the operations described in Li):
generate a preprocessed image pair by removing background areas around blades of a wind turbine from photographed images of the wind turbine captured by a drone (Abstract: “[i]In image stitching, a blurring of the image is carried out to reduce the influence of noise…To overcome these problems, a preprocessing method based on background removal is proposed”; Section II of Li discloses preprocessing to remove background images of the wind turbine before image stitching is performed; on page 174, under section I. Introduction, Li cites an article entitled "Autonomous Visual Inspection Of Large-Scale Infrastructures Using Aerial Robots", published in arXiv preprint arXiv:1901.05510 (2019) as teaching the photographs being preprocessed can be captured by a drone);
determine first initial match points in the preprocessed image pair by using a pre-trained deep learning module (section IIIB discusses performing initial point determination after preprocessing has been performed to match feature points; Li does not explicitly disclose using a pre-trained deep learning module for this purpose);
determine non-utilized match points out of the determined first initial match points by calculating the value of position change for each of the first initial match points between the images of the preprocessed image pair, and identifying the non-utilized match points based on a statistical analysis of the calculated value of position change (the BRI for the term “non-utilized match points” is that it means initial match points that will not be used in the final set of match point pairs that will be used during image stitching; section IIIC of Li discusses performing a Random Sample Consensus (RANSAC) algorithm to determine "the final matching feature points" as valid match points by excluding match points determined to be outliers; Li does not explicitly disclose identifying the non-utilized match points based on a statistical analysis of the calculated value of position change); and
determine valid match points by excluding the determined non-utilized match points from the determined first initial match points (section IIIC, the match points that are excluded in Li are the outliers that cannot be fitted to the model); and
perform image stitching between a plurality of images (section IIIC: “[a]fter the transformation matrix is obtained, the size of the stitched image and the overlap of the two images can be solved algebraically. In the non overlapping part, the gray value of the new image can be obtained based on the transformation matrix and interpolation method; in the overlapping area of two images, the weighted smoothing algorithm is used to realize the fusion transition between the two images”; Fig. 2 shows the stitching results),
wherein the statistical analysis of the calculated value of position change comprises an combined value of the calculated value of position change (Li does not explicitly disclose this limitation).
As indicated above, Li does not explicitly disclose that the initial match point determination uses a pre-trained deep learning module to determine the first initial match points. Wang, in the same field of endeavor, discloses using a pre-trained deep learning module to determine feature match points in images of rotor blades (paras. [0071]-[0073], one or more artificial neural networks 102, 304, 404, Figs. 1, 3, 5 and 8).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to use one or more of the artificial neural networks of Wang in the system of Li to determine the first initial match points. One of ordinary skill in the art would have been motivated to make the modification to benefit from the high accuracy and robustness that can be achieved using neural networks to perform feature extraction and matching. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods (programming one or more processors with suitable software to implement a neural network) to yield predictable results.
As indicated above, Li does not explicitly disclose the limitation of determining non-utilized match points by calculating the value of position change for each of the first initial match points between the images of the preprocessed image pair, and identifying the non-utilized match points based on a statistical analysis of the calculated value of position change.
Huang, in the same field of endeavor, discloses performing an “improved SIFT algorithm based on slope and distance ratio constraint (SDRC-SIFT)” that performs such a statistical analysis of the position change values. Section IIIC of Huang discloses that the SDRC-SIFT algorithm calculates the value of position change for each of the initial match points between the images of the preprocessed image pair by using equation 3 to calculate the slope, k, of the line interconnecting the position of an initial match point in a first image with the position of the same initial match point in a second image, as discussed in section IIIB of Huang. The slope k is based on the positions of the points and their respective x and y coordinate values, as indicated by equation 3 of Huang. It should be noted that a change in the position of point P1 while position P2 stays the same, or vice versa, will be reflected in a change in the slope k of the line interconnecting the points since the slope is based on the coordinates of the points. Therefore, calculating the slope k for each of the first initial match points between the images constitutes calculating a value of position change for each of the first initial match points between the images.
In Huang, the slope k is calculated and used in the process represented by the flowchart shown in Fig. 3 of Huang as a value upon which a determination is made as to whether a pair of initial match points is to be discarded, i.e., whether the pair is to be excluded as valid match points (Fig. 3 shows block labeled “feature point matching set, R,S” and the block that follows it labeled “calculate the slope k of the corresponding point pair”). Although Huang also uses the distance ratio, D, corresponding to the ratio of the distances between adjacent points in the same image in making the determination as to whether to discard an initial match point pair, Huang nonetheless uses the value of the slope k for each initial match point pair, which is reflective of a change in the position of points Pi and Pi’ of the corresponding initial match point pairs. Therefore, Huang teaches determining “non-utilized match points out of the determined first initial match points by calculating the value of position change for each of the first initial match points between the images of the preprocessed image pair…”.
Regarding the portion of the above-quoted limitation of “and identifying the non-utilized match points based on a statistical analysis of the calculated value of position change…”, Huang discloses that the “statistical histogram of K bins” is “based on the slope”, as stated in section III.C., step 4 of Huang. The statistical histogram is used in the process of identifying match points to be discarded, and therefore setting up the histogram bins based on the slope calculation and using the values in the histogram bins to determine which match point pairs should be discarded constitutes identifying the non-utilized match points based on a statistical analysis of the calculated value of position change.
Regarding the limitation of claim 1 of “wherein the statistical analysis of the calculated value of position change comprises a combined value of the calculated value of position change”, the BRI for this limitation is that the value of position change is calculated for each pair of the initial match points and that the combination of the calculated values of position change for each pair is considered in determining which pairs are to be excluded. The BRI is based on Figs. 5-6c and paras. [0145]-[0150] of the present disclosure.
This is also taught by Huang. The statistical analysis of Huang retains “the matching pair of points in the highest bin” of the statistical histogram. Since the histogram bins are based on the slope, and the slope is a calculated value of position change, and because the process is performed for the combination of all of the match point pairs, as indicated by the blocks labeled “i=i+1” and “j=j+1” in the flowchart of Fig. 3, the statistical analysis of Huang comprises a combined value of the calculated value of position change.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to further modify the system and methods of Li as modified by Wang based on the teachings of Huang to determine and exclude non-utilized match points based on the statistical histogram analysis of the position change values as taught by Huang. One of ordinary skill in the art would have been motivated to make the modification to improve the RANSAC method used in Li to use the additional slope constraint of Huang to “improve the matching efficiency and enhance the stability of the algorithm”, as taught by Huang. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (programming one or more processors with suitable software to implement the modified RANSAC algorithm of Huang).
Regarding claim 2, Li does not explicitly disclose determining first initial match points located within a predetermined distance from edges of the blades in the preprocessed image pair as the non-utilized match points. As indicated above in the Response to Arguments section of this Action, Wang discloses this limitation. In particular, Wang discloses excluding match points that are within a predetermined distance from the edges of the blades by detecting the contour of the blade (Fig. 8, step 704, para. [0075]), identifying the subset of image frames that correspond to a reference blade pose (Fig. 8, steps 706, 708 and 710, paras. [0076]-[0078]) and masking out points that are less than a predetermined distance from the contour (Fig. 8, steps 714 and 716, paras. [0079]-[0080]). The width of the masked portion of the contour corresponds to a predetermine distance from the blade edges and points that are less than this distance from the edges of the blade are non-utilized match points because they are masked out and therefore not utilized.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to further modify the system and methods of Li as modified based on the teachings of Huang and Wang to determine and exclude non-utilized match points within a predetermined distance from the blade contours as taught by Wang. One of ordinary skill in the art would have been motivated to make the modification to improve the efficiency and accuracy of the method used in Li by excluding points near the edges as taught by Huang. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods (programming one or more processors with suitable software to identify contours and mask out regions near the blade edges) to yield predictable results.
Regarding claim 3, the rejection of claim 1 applies mutatis mutandis to claim 3. As indicated above in that rejection, Huang teaches determining non-utilized match points based at least in part on the slope values.
Regarding claim 5, the claim has been amended to require only one of the steps labeled (1)-(3) and the claim does not indicate which step is required. Under MPEP 2111.04, claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. See, e.g., Fresenius USA, Inc. v. Baxter Int’l, Inc., 582 F.3d 1288, 1298, 92 USPQ2d 1163, 1171 (Fed. Cir. 2009). Therefore, the claim requires one or more of steps (1)-(3).
Regarding step (1), this limitation is recited in dependent claim 2, which is rejected above. Therefore, the rejections of claims 1 and 2 apply mutatis mutandis to claim 5 for the case where step (1) is performed.
Furthermore, for the case where step (2) is performed, the rejection of claim 1 applies mutatis mutandis because, as indicated above in the rejection of claim 1, Huang discloses using the slope values to identify match points that will not be utilized.
Regarding step (3), this limitation is recited in claim 1. Therefore, for the case where step (3) is performed, the rejection of claim 1 applies mutatis mutandis to claim 5.
Regarding the last, “wherein” limitation of claim 5, this carries no patentable weight because the recited sequence does not necessarily occur since steps (1)-(3) are claimed optionally.
Regarding claim 6, the claim is given no patentable weight because neither claim 5 nor claim 6 requires the determination of first and second non-utilized match points since steps (1)-(3) are claimed optionally in claim 5, which means that claims 5 and 6 require only the determination of first, second or third non-utilized match points. Consequently, the determination sequence recited in claim 6 for determining first candidate match points by excluding first and second non-utilized match points is also not required by the claim, and therefore is given no patentable weight.
Regarding claim 7, the claim is given no patentable weight because it recites excluding third non-utilized match points, but none of claims 5-7 require that step (3) be performed, which is the step that determines third non-utilized matching points. Regarding the claim 7 stitching limitation, this limitation is recited in claim 5, and therefore the rejection of claims 5 and 6 apply mutatis mutandis to claim 7.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Wang and Huang as applied to claims 1-3 and 5-7 above, and further in view of U.S. Publ. Appl. No. 2022/0215557 A1 to Xu et al. (hereinafter referred to as “Xu”).
Regarding the “at least one of” language used in claim 4, as indicated above, under MPEP 2111.04, claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed. In addition, when a claim requires selection of an element from a list of alternatives, the prior art teaches the element if one of the alternatives is taught by the prior art. Id. Therefore, the claim limitation “the combined value of the calculated value of position change comprises at least one of an average value, sum value, product value, variance value, and standard deviation value of the calculated value of position change” requires any one or more of the listed items (paras. [0116]-[0117]).
The combined teachings of Li, Wang and Huang do not explicitly teach that the calculated value of position change corresponding to the slope value k of Huang can comprise at least one of an average value, sum value, product value, variance value, and standard deviation value. Xu, in the same field of endeavor, discloses processing images to detect objects in the images while ignoring background in the images by performing an edge detection algorithm that detects edges of objects by determining candidate boundary lines, averaging the slopes of the candidate boundary lines to obtain an average slope, determining absolute values of differences between the slopes of the lines and the average slope, and determining that the line as a target boundary line when the difference is less than a threshold value.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to further modify the system and methods of Li as modified based on the teachings of Huang and Wang to use the average slope values corresponding to lines connecting the corresponding pairs of match points as an additional constraint in determining whether to exclude the match points as non-utilized match points as taught by Xu. One of ordinary skill in the art would have been motivated to make the modification to improve the RANSAC method used in Li to use average slope values in this manner in addition to using the Euclidian distance values to identify and exclude non-utilized match points as taught by Huang. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (programming one or more processors with suitable software to implement the modified RANSAC algorithm of Huang with the slope-averaging modification of Xu).
Claims 8 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Li in view of Wang and Huang as applied to claims 1-3 and 5-7 above, and further in view of U.S. Publ. Appl. No. 2021/0326601 A1 to Tang et al. (hereinafter referred to as “Tang”).
Regarding claim 8, the preamble language of “wherein if the number of the determined first candidate match points is less than or equal to the first reference number, the processor is further configured to” is given no patentable weight because neither claim 5 nor claim 6 requires the determination of first or second initial match points, from which the first candidate match points are determined through sequential exclusion, as discussed above in the rejection of claim 6.
Regarding the “cropped image pair” limitation of claim 8, as indicated above in the rejection of claims 1 and 5, Li discloses determining initial match points in an image pair by using pre-trained deep learning and determining valid match points based on the initial match points. However, the combined teachings of Li, Wang and Huang do not explicitly teach generating a cropped image pair, determining initial match points in the cropped image pair and determining valid match points based on the determined initial match points.
Tang, in the same field of endeavor, discloses determining initial match feature keypoints in an image pair (Figs. 2 and 3A, target image 202, 308 and query image 200, 306) that is cropped (para. [0076]), generating keypoint scores for the initially matched pairs of keypoints using pre-trained deep learning, and determining which of the initial match feature keypoints are valid match keypoints based on the keypoint scores (valid match points are referred in Tang as “reliable keypoints”; Fig. 3A, paras. [0041]-[0045]).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to further modify the system and methods of Li as modified based on the teachings of Huang and Wang to crop image pairs before performing matching of points in image pairs as taught by Tang. One of ordinary skill in the art would have been motivated to make the modification to improve the RANSAC method used in Li to use cropped images in order to isolate regions of interest, remove background noise and reduce image processing overhead by reducing the number of pixel values that have to be processed. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (programming one or more processors of Li with suitable software to perform image cropping as part of, or as a precursor to, the modified RANSAC algorithm of Huang).
Regarding claim 9, the BRI for this claim is that candidate match points are determined by excluding non-utilized match points that are determined based on contours of the blades and by excluding non-utilized match points that are determined based on the absolute values of slopes between corresponding match points in the cropped image pair. It should be noted that claim 9 requires that these determinations and exclusions be performed “in sequence”, but does specify any order for the sequence.
The rejections of claims 1, 2, 3 and 8 apply mutatis mutandis to claim 9. As indicated above in those rejections, the combined teachings of Li, Wang, Huang and Tang teach determining candidate match points by excluding non-utilized match points in cropped image pairs based on slope and based on blade contours.
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the present disclosure, to further modify the system and methods of Li as modified based on the teachings of Huang, Wang and Tang to exclude non-utilized match points in sequence based on slope and based on blade contours. One of ordinary skill in the art would have been motivated to make the modification to improve the robustness of the RANSAC method used in Li by excluding non-utilized match points based on slope and based on blade contours since both methods of exclusion are known in the art to be beneficial. The modification could have been made by one of ordinary skill in the art before the effective filing date of the present disclosure with a reasonable expectation of success because making the modification merely involves combining prior art elements according to known methods to yield predictable results (programming one or more processors of Li with suitable software to perform exclusions based also on slope and blade contours).
Allowable Subject Matter
Claim 10 is 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.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 10, none of the art of record teaches or suggests further excluding non-utilized match points based on degree of position change after exclusion has already been performed based on slope and blade contours if the number of match points remaining after those exclusions exceeds a predetermined number.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DANIEL J SANTOS whose telephone number is (571)272-2867. The examiner can normally be reached M-F 9-5.
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/DANIEL J. SANTOS/Examiner, Art Unit 2667
/MATTHEW C BELLA/Supervisory Patent Examiner, Art Unit 2667
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