DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on June 11th, 2025 has been considered and the listed references were noted.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character(s) not mentioned in the description: 1 and 2 in Figure 3; 1-5 in Figure 4.
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
The drawings are objected to because Figure 2 has blurry, unreadable text in numerous boxes in the flowchart (such as the gray text in Resizing, Oriented FAST Detector, Multi-Probe LSH, etc.).
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
Applicant is reminded of the proper content of an abstract of the disclosure.
A patent abstract is a concise statement of the technical disclosure of the patent and should include that which is new in the art to which the invention pertains. The abstract should not refer to purported merits or speculative applications of the invention and should not compare the invention with the prior art.
If the patent is of a basic nature, the entire technical disclosure may be new in the art, and the abstract should be directed to the entire disclosure. If the patent is in the nature of an improvement in an old apparatus, process, product, or composition, the abstract should include the technical disclosure of the improvement. The abstract should also mention by way of example any preferred modifications or alternatives.
Where applicable, the abstract should include the following: (1) if a machine or apparatus, its organization and operation; (2) if an article, its method of making; (3) if a chemical compound, its identity and use; (4) if a mixture, its ingredients; (5) if a process, the steps.
Extensive mechanical and design details of an apparatus should not be included in the abstract. The abstract should be in narrative form and generally limited to a single paragraph within the range of 50 to 150 words in length.
See MPEP § 608.01(b) for guidelines for the preparation of patent abstracts.
The abstract of the disclosure is objected to because it is over 150 words (173 words). A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
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 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over Hurley et al. (US 2012/0281883), in view of Fredrich et al. (US 2014/0270394), Varfolomee et al. (WO 2017039475 A1), and Howse et al. (Learning Open CV 4 Computer Vision with Python 3).
Regarding Claim 1, Hurley discloses “An automatic tracking method for co-registration of two-dimensional (2D) Scanning Electron Microscopy (SEM) images and three-dimensional (3D) tomographic data of a rock cylinder, comprising the steps of:” (Hurley, Paragraph [0005], discloses “According to some embodiments, a method of constructing a model of a sample of porous media is described. The method includes: receiving low resolution image data generated using a lower resolution measurement performed on a sample of the porous media; receiving high resolution image data representing characterizations of aspects (such as shape, size and spacing of pores, etc.) of a smaller sample of the porous media, the high resolution data being generated using a higher resolution measurement performed on the smaller sample; and distributing the characterizations of aspects of smaller sample from the high resolution data into the low resolution data thereby generating an enhanced model of the porous media.”; Paragraph [0007], discloses “According to some embodiments, the high resolution image data is generated using one or more measurements such as: laser scanning fluorescent microscopy, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, vertical-scanning interferometry, nanoCTscans, and focused ion beam-scanning electron microscopy, and the low resolution image data is generated using one or more measurements such as: three dimensional micro CT, three dimensional conventional CT and three dimensional synchrotron CT scans, and macro digital photography.”); “(i) pre-processing one or more images acquired by SEM by reducing the spatial resolution and one or more images acquired by microtomography” (Hurley, Paragraph [0006], discloses “According to some embodiments the distributing includes using a multi-point statistical method, such as discrete variable geostatistics, or continuous variable geostatistics. According to some embodiments, the porous media is a hydrocarbon bearing subterranean rock formation. According to some embodiments, prior to the distributing, the low resolution image data is segmented into a binary image, the segmentation being based in part of the characterizations from high resolution measurement.”; Paragraph [0009] discloses “According to some embodiments a method of segmenting a digital image of porous media is described. The method includes: receiving a low resolution digital image generated using a lower resolution measurement performed on a first sample of the porous media; receiving a high resolution digital image generated using a higher resolution measurement performed on a small second sample of the porous media; identifying macropores from the high resolution digital image; and segmenting the low resolution digital image thereby generating a binary digital image having two possible values for each pixel, the segmenting being based on the identified macropores.”; Recall from Paragraph [0007] discloses low-resolution image data being generated by micro-CT, which according to Paragraph [0006] and [0009] are being pre-processed) “with the application of one or more image filters, followed by the application of a keypoint detection technique for comparison between the 2D SEM image and sequential sections of the microtomographic volume” (Hurley, Paragraph [0023], discloses “According to some embodiments, a combination is described of (a) high-resolution 2D or 3D LSFM images, acquired for REA's or REV's in rocks, with (b) CT scans, which capture relatively larger 3D volumes at lower resolution. LSFM scans are used as training images for 2D or 3D multi-point statistics to distribute high-resolution micropores throughout lower-resolution CT scan volumes, which are used as hard data to condition the simulations. The end result is a composite 3D "total porosity" model that captures large and small pores. An advantage of the technique is that high-resolution data helps solve the segmentation problem for CT scan data.”; Paragraph [0031] discloses “Confocal microscopy, the most common type of LSFM, uses point illumination and a pinhole placed in front of a detector to eliminate out-of-focus light. Because each measurement is a single point, confocal devices perform scans along grids of parallel lines to provide 2D images of sequential planes at specified depths within a sample.”)
Hurley does not explicitly disclose “to create a correspondence graph; (ii) internal orthogonal search from the correspondence graph created in step (i), where the correspondence points are calculated for all sections orthogonal to the main axis of the micro-computed tomography (micro-CT) image acquired from the rock cylinder; (iii) external multi-angle search in a subvolume of the external radius of the main axis of the cylinder from the correspondence plane with the largest number of pairs of keypoints defined by comparing the images among those that make up the micro-CT volume (3D) pairwise with the SEM images (2D) and considered as inliers to the homography obtained by the internal orthogonal search”. However, in an analogous field of endeavor, Fredrich discloses for creating a correspondence graph that “FIG. 9 is a diagram that illustrates an example of a rock sample and an example of a plot of the difference values, according to an embodiment of the invention.” (Fredrich, Paragraph [0024] and Figure 9 (see below))
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Here, the correspondence graph is clearly show according to the characteristics of the rock sample in terms of its porosity and domain size. Fredrich also discloses another correspondence graph in Figure 11, stating it “is a diagram that illustrates an example of an x-ray tomographic image and an example of a plot to assess anisotropy, according to an embodiment of the invention.” (Fredrich, Paragraph [0053] and Figure 11).
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Finally, Fredrich discloses for the internal orthogonal search that “According to alternative embodiments of the invention, the testing tool can be configured to analyze anisotropy within the digital volume by conducting the REV analysis in orthogonal directions. For example, the testing tool can be configured to conduct REV analysis by selecting adjacent test volumes aligned in the x-direction. The testing tool can then be configured to conduct REV analysis by selecting adjacent test volumes aligned in the z-direction. The testing tool can then compare the plots of the mean difference value percentage or the cumulative mean difference value percentage for each direction. If anisotropy is present within the volume, there is a difference in the shape of the mean (or cumulative mean) difference curves for each direction. FIG. 11 illustrates an example of an x-ray tomographic image along with a corresponding covariance plot in order to assess such anisotropy, according to an example implementation. The left-hand pane of FIG. 11 shows an x-ray tomographic image volume that exhibits layering heterogeneity in the x-direction; this x-ray tomographic image has a resolution of 13.6 microns per voxel. The right-hand pane of FIG. 11 shows the results of an implementation of the testing tool according to an implementation that assesses anisotropy, by way of a plot of coefficient of variation for probe directions along each of the x-axis and the z-axis. In this example, a covariance in grayscale values (COV) is computed, rather than a material property directly. Representative elementary volume analysis shows that porosity uncertainty in the z-direction decreases as volume size increases. However, porosity uncertainty in the x-direction is impacted by the heterogeneity in the sample, which is occurring on the length scale of sedimentary layering. While the covariance drops significantly with domain size along the z-direction, covariance varies with domain size along the x-direction in response to the layering heterogeneity. Comparison of these covariance characteristics demonstrates the presence of anisotropy within the image volume.” (Fredrich, Paragraph [0053] and Figure 11 (see above / previous page)) From this paragraph, we see that the REV analysis correlates closely to internal orthogonal search since it is being done in the orthogonal directions of the digital tomographic image volume in order to develop the correspondence points that are being plotted on the graph seen in Figure 11. The rock cylinder is not explicitly disclosed here in this paragraph, but it is still a rock sample that is being analyzed. A cylindrical-based rock sample will be further disclosed later on in the analysis with Varfolomee. Therefore, it would have been obvious for one of ordinary skill in the art to combine the automatic tracking method and preprocessing steps seen in Hurley with the creation of the correspondence graph seen in Fredrich in order to ensure an appropriate analysis of rock samples being observed before drilling into specific landscapes. By combining the automatic tracking and preprocessing methods seen in Hurley with the correspondence graphs of Fredrich, one of ordinary skill in the art allows for the user to have a clearer interpretation of the rock sample before being analyzed further for co-registration. Therefore, it would have been obvious to use the Hurley and Fredrich references to achieve the same limitations described in Claim 1.
The combination of Hurley and Fredrich does not explicitly disclose “(iii) external multi-angle search in a subvolume of the external radius of the main axis of the cylinder from the correspondence plane with the largest number of pairs of keypoints defined by comparing the images among those that make up the micro-CT volume (3D) pairwise with the SEM images (2D) and considered as inliers to the homography”. However, in an analogous field of endeavor, Varfolomee discloses the following for the multi-angle search in Columns 6 and 7:
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As we can see from the passage, the rock cylinder is now disclosed, and the cylinder is being analyzed at a specific surface (which, using BRI, can classify as a plane) to determine the coordinates (which, using BRI, can be considered keypoints). The side surface seems to have a large number of coordinates compared to the surface area of the cylinder without the side surfaces, and the euler angles of the cylinder are also being determined to ensure that all the spatial transformation parameters are found. Varfolomee also discloses the following in Column 5:
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This paragraph clearly describes the subvolume of the external radius of the main axis of the cylinder, as the rock cylinder at a fixed radius is described from previously, so having this volume measurement helps with the multi-angle search. Finally, Varfolomee discloses the following in Column 13:
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As we can see, the 2D SEM images are being compared with the 3D micro-CT volume in order to determine the overlapping region. Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of Hurley and Fredrich with the external multi-angle search techniques from Varfolomee to ensure a more complete automatic tracking method and achieve the above-described limitations seen in Claim 1.
The combination of Hurley, Fredrich, and Varfolomee does not explicitly disclose “and considered as inliers to the homography”. However, in an analogous field of endeavor, Howse discloses the following in Chapter 7, Pages 253-254:
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Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of Hurley, Fredrich, and Varfolomee with the Howse technique of considering inliers to the homography to achieve a robust automatic tracking method. By combining the automatic tracking method seen in the combination of Hurley, Fredrich, and Varfolomee with the Howse technique of considering inliers, one of ordinary skill in the art allows for a user of the method to appropriately fit the SEM and microCT images together effectively. Therefore, it would have been obvious for one of ordinary skill in the art to combine the Hurley, Fredrich. Varfolomee, and Howse references to achieve the same method described in Claim 1.
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Regarding Claim 8, the combination of Hurley, Fredrich, Varfolomee, and Howse discloses “The method according to claim 1, wherein the pairs of keypoints considered as inliers to the homography are determined by the Random Sample Consensus (RANSAC) instruction set.” (Howse, Chapter 7, Pages 253-254, discloses:
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). The proposed combination as well as the motivation for combining the Hurley, Fredrich, Varfolomee, and Howse references presented in the rejection of Claim 1, apply to Claim 8 and are incorporated herein by reference. Thus, the method recited in Claim 8 is met by Hurley, Fredrich, Varfolomee, and Howse.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of Mihara et al. (US 2017/0129780).
Regarding Claim 2, the combination of Hurley, Fredrich, Varfolomee, and Howse (Which will from hereon be described as “the combination of HFVH”) discloses “The method according to claim 1” (Please refer to the above-described analysis for Claim 1); the dark side where the luminance value is low exceeds 20% and the value of a point at which the frequency exceeds 50%, and the luminance value at the time of setting the frequency to 0% is calculated from the formula of the straight line thus obtained (the x fragment is calculated when the luminance and the frequency are regarded as x and y, respectively). A group of pixels having lower luminance values than the resultant luminance value represents the carbon crystal grain. Here, among the group of pixels, less than 30 pixels which are recognized as noises are excluded from those representing the carbon crystal grain.” (Mihara, Paragraph [0035]). From here, we can see that the contrast is being observed in the black carbon image, and is then being filtered out depending on the luminance of the sample when an image is acquired. If the threshold reaches a specific amount, it filters those set of pixels that do not correspond with what is found. Non local means is also described here as the noise is being excluded from the image to thus make it sharper. Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of HFVH with the technique of using applying image filters in the sequence (CLAHE, brightness, contrast, non-local means) seen in Mihara to achieve an improved automatic tracking method. By combining the automatic tracking method seen in the combination of HFVH with the image filtering technique seen in Mihara, one of ordinary skill in the art can allow for clearer and more sharper images when performing analysis on the SEM and microtomographic images of the rock cylinder sample. Therefore, it would have been obvious for one of ordinary skill of the art to combine the Hurley, Fredrich, Varfolomee, Howse, and Mihara references to achieve the same method described in Claim 2.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of Okajima et al. (JP 7076052 B1).
Regarding Claim 4, the combination of HFVH discloses “The method according to claim 1” (Please refer to the above-described analysis regarding Claim 1); surrounded by the minimum value of the Y coordinate of the upper portion of the contour line and the maximum value of the Y coordinate of the lower portion of the contour line as indicated by a block of a chain line on the image 104 illustrated in FIG. 6, for example (Step S 4). Next, the extraction unit 12 cuts out the image in the selected region (step S5). An image 105 illustrated in FIG. 7 is a cut-out image, and in the present exemplary embodiment, the image 105 cut out by the extraction unit 12 is referred to as a region image.” (Okajima, Paragraph [0017]). The extraction unit performing edge detection and cutting processes on the extracted image to form a region image is an example of a pre-processed image. Okajima further discloses “Machine learning converts individual images into local feature values SIFT, ORB (Oriented FAST and Rotated BRIEF), and AKAZE (Accelerated KAZE), Using a support vector machine or random forest for porosity as a codebook via BoVW (Bag of Visual Words) with a cluster count of 512. Note that a vector obtained by adding local feature values such as ORB, AKAZE, and SIFT may be associated with the porosity to perform machine learning” (Okajima, Paragraph [0030]). Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of HFVH with the technique of inputting preprocessed images into the ORB algorithm seen in Okajima to achieve an improved automatic tracking method for analyzing rock cylinders. By using the ORB algorithm, one of ordinary skill in the art permits features to be extracted from the acquired and preprocessed images to determine different mineralogical characteristics of the rock sample upon further analyses. Therefore, it would have been obvious for one of ordinary skill in the art to combine the Hurley, Fredrich, Varfolomee, Howse, and Mihara references in order to achieve the same claim described in Claim 4.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of He et al. (CN 109949348 A).
Regarding Claim 5, the combination of HFVH discloses “The method according to claim 1” (Please refer to the above-described analysis for Claim 1); wherein binary vectors describing these keypoints are generated with the rotated Binary Robust Independent Elementary Features (rBRIEF) method”. The combination of HFVH is not relied on to disclose “wherein binary vectors describing these keypoints are generated with the rotated Binary Robust Independent Elementary Features (rBRIEF) method”. However, in an analogous field of endeavor, He discloses the following in Paragraphs [0043]-[0045]:
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Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of HFVH with the He technique of generating binary vectors using the rBRIEF method to achieve the same method seen in Claim 5.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of He and Long et al. (US 9672358 B1).
Regarding Claim 6, the combination of Hurley, Fredrich, Varfolomee, Howse, and He (Which, from hereon, will be described as “the combination of HFVHH”) discloses “The method according to claim 5” (Please refer to the above-described analysis regarding Claim 5); (Hurley, Paragraph [0007], discloses “According to some embodiments, the high resolution image data is generated using one or more measurements such as: laser scanning fluorescent microscopy, scanning electron microscopy, transmission electron microscopy, atomic force microscopy, vertical-scanning interferometry, nanoCTscans, and focused ion beam-scanning electron microscopy, and the low resolution image data is generated using one or more measurements such as: three dimensional micro CT, three dimensional conventional CT and three dimensional synchrotron CT scans, and macro digital photography.”) nearest neighbor index, the vector neighbor module 112 can, substantially in real-time, organize and/or process the binary vectors such that the malware matching module 114 can infer the nearest neighbors of each binary vector based on distances between the binary vectors. In some implementations, the vector neighbor module 112 can use Fast Library for Approximate Nearest Neighbors (FLAAN) techniques to determine the nearest neighbors of the binary vector. For example, in some instances, a Hamming function can be used to calculate a distance between two binary vectors (i.e., a received input sample and a stored known sample). Hamming distances (i.e., the distance computed by the Hamming function) can be calculated for each binary vector from a set of binary vectors stored in the malware detection database 108 as compared to the binary vector of the input sample. A FLANN function can then use the Hamming distances to identify the nearest neighbors to the input sample. In other implementations, other suitable processes, such as, for example, a pHash function, a scale-invariant feature transform (SIFT) function and/or the like, can be used to determine the nearest neighbors of the binary vector” (Long, Col 8, Lines 46-67; Col 9, lines 1-8). Here, we see a clear example of binary vectors being compared to one another. Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in the combination of HFVHH with the Long technique of binary vectors being compared to one another to achieve the same method described in Claim 6.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of Scheidegger et al. (US 20220292633 A1).
Regarding Claim 7, the combination of HFVH discloses “The method according to claim 1” (Please refer to the above-described analysis regarding Claim 1), (Scheidegger, Paragraph [0063]). Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the automatic tracking method seen in HFVH with the Scheidegger technique of using filtering correlations using the Lowe Ratio Test to achieve the same method described in Claim 7.
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Hurley in view of Fredrich, Varfolomee, and Howse, and further in view of Lowe (Distinctive Image Features from Scale-Invariant Keypoints).
Regarding Claim 15, the combination of HFVH discloses “The method according to claim 1” (Please refer to the above-described analysis for Claim 1); Page 97:
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Here, although the keypoints along the edge are removed, the keypoints of the along the edge of an object of an image were still being detected. Therefore, it would have been obvious for one of ordinary skill in the art before the effective filing date of the claimed invention to combine the method seen in the combination of HFVH with the Lowe technique of detecting keypoints along the edge to result in an improved automatic tracking method. By combining the method seen ibn HFVH with the Lowe technique of detecting keypoints along the edge, one of ordinary skill in the art can create a more effective correspondence graph when analyzing the rock cylindrical sample. Therefore, it would have been obvious for one of ordinary skill in the art to combine the Hurley, Fredrich, Varfolomee, and Howse references to achieve the same method described in Claim 15.
Allowable Subject Matter
Claim 3 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: For Claim 3, the combination of HFVHH does not explicitly disclose a mask for low transmittance minerals that can generate artifacts in tomographic images, given the relative density contrast with the main mineralogical assembly, being applied to the SEM images to avoid the concentration of keypoints mainly in these minerals. None of the cited prior art references provide a motivation to teach the ordered combination of the limitations recited in the claim in combination with the claim limitations of Claim 3.
Claims 9-11 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: For Claim 9, the combination of HFVHH does not explicitly disclose the correspondence graph being created with the training images (microtomography) on the abscissa axis and the points considered as inliers. None of the cited prior art references provide a motivation to teach the ordered combination of the limitations recited in the claim in combination with the claim limitations of Claim 9.
For Claim 10, the combination of HFVHH does not explicitly disclose the internal orthogonal search having a search for keypoints among the SEM and micro-CT images is restricted to the internal concentric region of the cylinder. None of the cited prior art references provide a motivation to teach the ordered combination of the limitations recited in the claim in combination with the claim limitations of Claim 10. Claim 11 includes the above-described allowable subject matter due to its dependency from Claim 10, either directly or indirectly.
Claims 10-11 are objected to as being dependent upon a rejected base claim, but
would be allowable if rewritten in independent form including all of the limitations of the
base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: For Claim 10, the combination of HFVHH does not explicitly disclose the internal orthogonal search having a search for keypoints among the SEM and micro-CT images is restricted to the internal concentric region of the cylinder. None of the cited prior art references provide a motivation to teach the ordered combination of the limitations recited in the claim in combination with the claim limitations of Claim 10. Claim 11 includes the above-described allowable subject matter due to its dependency from Claim 10, either directly or indirectly.
Claims 12-14 are objected to as being dependent upon a rejected base claim, but
would be allowable if rewritten in independent form including all of the limitations of the
base claim and any intervening claims. The following is a statement of reasons for the indication of allowable subject matter: For Claim 12, the combination of HFVHH does not explicitly disclose the external multi-angle search being divided into two sequential phases called gross multi-angle search and fine-tuning search. None of the cited prior art references provide a motivation to teach the ordered combination of the limitations recited in the claim in combination with the claim limitations of Claim 12. Claims 13 and 14 include the above-described allowable subject matter due to their dependencies from Claim 12, either directly or indirectly.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Varslot et al. (US 20150104078 A1) teaches a method for processing image data of a sample.
Schoenmaker et al. (US 20180082444 A1) teaches Methods of investigating a specimen using tomographic imaging.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SORIE I KOROMA JR whose telephone number is (571)272-9259. The examiner can normally be reached Monday - Friday 8AM-6:00PM; Alternate Fridays Off.
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/SORIE I KOROMA JR/Examiner, Art Unit 2662
/AMANDEEP SAINI/Supervisory Patent Examiner, Art Unit 2662
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