CTNF 19/231,923 CTNF 77425 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia 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 (IDS) submitted on 6/9/25, 7/16/25 and 2/18/26 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement has been considered by the examiner. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-21-aia AIA Claim s 1, 10-15 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Grundhofer (US 2017/0070711) in view of Vora (US 2019/0331497) . Regarding claim 1, Grundhofer discloses a system comprising: an illumination device configured to sequentially illuminate a surface in a plurality of colors (paragraph [27], Grundhofer discloses elements 102 and 104 for sequentially illuminating light patterns on a surface, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights); a monochromatic image sensor configured to capture a plurality of image frames of the surface as the surface is sequentially illuminated in the plurality of colors by the illumination device (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights); and a computing device including at least one memory storing instructions (paragraph [69], Grundhofer discloses memory for storing computer program instructions to be executed by a computer processor), and at least one processor coupled to the at least one memory for executing the instructions to perform operations (paragraph [69], Grundhofer discloses memory for storing computer program instructions to be executed by a computer processor), the operations including: receiving the plurality of image frames from the monochromatic image sensor (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights), each of the plurality of image frames comprising a plurality of pixels (paragraph [36], Grundhofer discloses that captured images comprise a plurality of pixels). Grundhofer does not disclose identifying, in each of the plurality of image frames, a pixel block comprising a subset of the plurality of pixels associated with a target feature; generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels within the pixel block identified in each of the plurality of image frames; and generating, based on the plurality of pixel intensity maps, relative pixel blocks across the plurality of image frames, the relative pixel blocks representing the target feature in the plurality of image frames. However, Vora teaches identifying, in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), a pixel block comprising a subset of the plurality of pixels associated with a target feature (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted); generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels within the pixel block identified in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground); and generating, based on the plurality of pixel intensity maps (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), relative pixel blocks across the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), the relative pixel blocks representing the target feature in the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for improving computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Regarding claim 10, Grundhofer discloses generating a color image from the plurality of image frames (paragraph [27], Grundhofer discloses elements 102 and 104 for sequentially illuminating light patterns on a surface, and that camera 106 is configured to capture color images, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights) based on the relative pixel blocks (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground). Regarding claim 11, Grundhofer does not disclose wherein the target feature is positioned at a different location in each of the plurality of image frames, indicative of motion between the plurality of image frames, and the operations further include determining the motion based on a comparing of the relative pixel blocks. However, Vora teaches wherein the target feature is positioned at a different location in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), indicative of motion between the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and wherein motion or “sweep movement” is indicated with longitudinal, lateral, diagonal and/or rotational movements of the first intensity map over the second intensity map, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), and the operations further include determining the motion based on a comparing of the relative pixel blocks (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and wherein motion or “sweep movement” is indicated with longitudinal, lateral, diagonal and/or rotational movements of the first intensity map over the second intensity map, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for improving computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Regarding claim 12, Grundhofer discloses wherein each of the plurality of image frames is captured by the monochromatic image sensor as the surface is illuminated in a different color of the plurality of colors by the illumination device (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104). Regarding claim 13, Grundhofer discloses wherein the plurality of image frames include a first image frame associated with a first color of the plurality of colors (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104), a second image frame associated with a second color of the plurality of colors (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104), and a third image frame associated with a third color of the plurality of colors (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104). Regarding claim 14, Grundhofer discloses wherein the plurality of colors include at least one of red, green, or blue (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104). Regarding claim 15, Grundhofer discloses a computing device comprising: at least one memory storing instructions (paragraph [69], Grundhofer discloses memory for storing computer program instructions to be executed by a computer processor); and at least one processor coupled to the at least one memory for executing the instructions to perform operations (paragraph [69], Grundhofer discloses memory for storing computer program instructions to be executed by a computer processor), the operations including: receiving, from a monochromatic image sensor (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights), a plurality of image frames of a surface captured by the monochromatic image sensor as the surface is sequentially illuminated in a plurality of colors by an illumination device (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights), each of the plurality of image frames comprising a plurality of pixels (paragraph [36], Grundhofer discloses that captured images comprise a plurality of pixels). Grundhofer does not disclose identifying, in each of the plurality of image frames, a subset of the plurality of pixels including a target feature; generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels in each of the plurality of image frames; and identifying, based on a comparing of the plurality of pixel intensity maps, one or more matching pixels across each of the plurality of image frames, the one or more matching pixels representing the target feature in each of the plurality of image frames. However, Vora teaches identifying, in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), a subset of the plurality of pixels including a target feature (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted); generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground); and identifying, based on a comparing of the plurality of pixel intensity maps (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), one or more matching pixels across each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), the one or more matching pixels representing the target feature in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for improving computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Regarding claim 18, Grundhofer discloses generating color image (paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights, in that paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104). Grundhofer does not disclose generating relative pixel blocks for the plurality of image frames including the one or more matching pixels across each of the plurality of image frames, wherein the relative pixel blocks are used for generating a color image from the plurality of image frames or determining a motion associated with the target feature between the plurality of image frames. However, Vora teaches generating relative pixel blocks for the plurality of image frames including the one or more matching pixels across each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), wherein the relative pixel blocks are used for generating an image from the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground) or determining a motion associated with the target feature between the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and wherein motion or “sweep movement” is indicated with longitudinal, lateral, diagonal and/or rotational movements of the first intensity map over the second intensity map, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted). Since Grundhofer discloses generating a color image, and Vora discloses “wherein the relative pixel blocks are used for generating an image from the plurality of image frames”, therefore, by simple substitution, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for ascertaining the limitation “wherein the relative pixel blocks are used for generating a color image from the plurality of image frames” in order to improve computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Regarding claim 19, Grundhofer discloses a computer-implemented method comprising: receiving, from a monochromatic image sensor (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights), a first image frame and a second image frame of multimodal spectrum captured by the monochromatic image sensor (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural or multiple color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights), each of the first image frame and the second image frame (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural or multiple color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights) comprising a plurality of pixels (paragraph [36], Grundhofer discloses that captured images comprise a plurality of pixels). Grundhofer does not disclose identifying a first pixel block in the first image frame and a second pixel block in the second image frame, each of the first pixel block and the second pixel block comprising a subset of the plurality of pixels associated with a target feature in the first image frame or the second image frame, respectively; generating a first pixel intensity map based on first pixel intensity data of the first pixel block; generating a second pixel intensity map based on second pixel intensity data of the second pixel block; and identifying, based on a comparing of the first pixel intensity map and the second pixel intensity map, one or more matching pixels across the first pixel block and the second pixel block, the one or more matching pixels representing the target feature in each of the first image frame and the second image frame. However, Vora teaches identifying a first pixel block in the first image frame and a second pixel block in the second image frame (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), each of the first pixel block and the second pixel block comprising a subset of the plurality of pixels associated with a target feature in the first image frame or the second image frame (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), respectively (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground); generating a first pixel intensity map based on first pixel intensity data of the first pixel block (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region); generating a second pixel intensity map based on second pixel intensity data of the second pixel block (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region); and identifying, based on a comparing of the first pixel intensity map and the second pixel intensity map (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), one or more matching pixels across the first pixel block and the second pixel block (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground), the one or more matching pixels representing the target feature in each of the first image frame and the second image frame (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for improving computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Regarding claim 20, Grundhofer discloses generating a color image from the first image frame and the second image frame (paragraph [27], Grundhofer discloses implementing monochromatic camera or image sensor for capturing plural color images based on sequentially illuminating light patterns on a surface by elements 102 and 104, wherein paragraph [26], Grundhofer discloses elements 102 and 104 sequentially illuminate light patterns onto a surface in colors of red, green and blue with differing intensities of colored lights). Grundhofer does not disclose generating a color image from the first image frame and the second image frame using the one or more matching pixels; or determining a motion associated with the target feature between the first image frame and the second image frame using the one or more matching pixels. However, Vora discloses using one or more matching pixels (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, wherein paragraph [27], Vora disclose capturing a plurality of images from above the ground); or determining a motion associated with the target feature between the first image frame and the second image frame using the one or more matching pixels (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and wherein motion or “sweep movement” is indicated with longitudinal, lateral, diagonal and/or rotational movements of the first intensity map over the second intensity map, and thus providing a first cell with relative pixel blocks and a second cell with relative pixel blocks for identifying a fixed point to compare with a reference point to identify a target feature when comparing pixel maps, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted). Since Grundhofer discloses “generating a color image from the first image frame and the second image frame”, and Vora discloses “…using one or more matching pixels”, therefore, by simple substitution, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for ascertaining the limitation “generating a color image from the first image frame and the second image frame using the one or more matching pixels” in order to improve computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]) . 07-21-aia AIA Claim s 2 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Grundhofer (US 2017/0070711) and Vora (US 2019/0331497) in view of Yajko (US 2017/0132799) . Regarding claim 2, Grundhofer and Vora does not disclose wherein generating the plurality of pixel intensity maps includes: for the pixel block identified in each of the plurality of image frames, performing edge detection filtering on the pixel block to generate an edge converted pixel block; and generating a corresponding pixel intensity map, of the plurality of pixel intensity maps, for each frame based on pixel intensity data of the edge converted pixel block. However, Yajko teaches wherein generating the plurality of pixel intensity maps (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps) includes: for the pixel block identified in each of the plurality of image frames (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps for a plurality of images), performing edge detection filtering on the pixel block to generate an edge converted pixel block (paragraph [42], Yajko discloses edge enhancement filtering can be applied for performing edge detection filtering to smooth out edges or sharpening edges depending on the task at hand); and generating a corresponding pixel intensity map (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps for a plurality of images), of the plurality of pixel intensity maps (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps for a plurality of images), for each frame based on pixel intensity data of the edge converted pixel block (paragraph [42], Yajko discloses edge enhancement filtering can be applied for performing edge detection filtering to smooth out edges or sharpening edges depending on the task at hand for enhancing the edges of an object within an image). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for Grundhofer, Vora and Yajko together as a whole for providing quick, real-time image processing to obtain high quality images in a fast manner (Yajko’s paragraph [5]). Regarding claim 16, Grundhofer does not disclose wherein generating the plurality of pixel intensity maps includes: for the subset of the plurality of pixels identified in each of the plurality of image frames. However, Vora teaches wherein generating the plurality of pixel intensity maps (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps) includes: for the subset of the plurality of pixels identified in each of the plurality of image frames (paragraph [46], Vora discloses generating a first pixel intensity map base on first pixel or cell and generating a second pixel intensity map based on second pixel or cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for improving computer processing and efficiency for estimating an object or vehicle location without placing undue requirements to generate high-definition maps of the localization of the vehicle or object (Vora’s paragraph [26]). Grundhofer and Vora do not disclose performing edge detection filtering on the subset of the plurality of pixels to generate an edge converted pixel block; and generating a corresponding pixel intensity map, of the plurality of pixel intensity maps, for each frame based on pixel intensity data of the edge converted pixel block. However, Yajko teaches performing edge detection filtering on the subset of the plurality of pixels to generate an edge converted pixel block (paragraph [42], Yajko discloses edge enhancement filtering can be applied for performing edge detection filtering to smooth out edges or sharpening edges depending on the task at hand); and generating a corresponding pixel intensity map (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps for a plurality of images), of the plurality of pixel intensity maps (paragraph [56], Yajko discloses generating maps of intensity values of a number of pixels of a digital image to generate pixel intensity maps for a plurality of images), for each frame based on pixel intensity data of the edge converted pixel block (paragraph [42], Yajko discloses edge enhancement filtering can be applied for performing edge detection filtering to smooth out edges or sharpening edges depending on the task at hand for enhancing the edges of an object within an image). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer and Vora together as a whole for Grundhofer, Vora and Yajko together as a whole for providing quick, real-time image processing to obtain high quality images in a fast manner (Yajko’s paragraph [5]) . 07-21-aia AIA Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Grundhofer (US 2017/0070711) and Vora (US 2019/0331497) in view of Ha (US 2022/0187584) . Regarding claim 3, Grundhofer discloses generating the plurality of pixel intensity maps (paragraph [46], Vora discloses generating a first pixel intensity map base on first cell and generating a second pixel intensity map based on second cell, in that a cell can comprise a plurality of pixels with the target region, and paragraph [49], Vora discloses comparing the first pixel intensity map with second intensity map for identifying the best match for identifying a feature that is targeted, thus providing a plurality (ie. two or more) of pixel intensity maps). Grundhofer and Vora does not disclose normalizing the pixel intensity values of the plurality of image frames prior to generating the plurality of pixel intensity maps. However, Ha teaches normalizing the pixel intensity values of the plurality of image frames (paragraph [37], Ha discloses normalizing the intensity of each image in the plurality of images). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Grundhofer, Vora and Ha together as a whole for producing higher quality images for viewing when performing examinations of specimens . Double Patenting 08-33 AIA The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg , 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman , 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi , 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum , 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel , 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington , 418 F.2d 528, 163 USPQ 644 (CCPA 1969). A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA. A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b). The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13. The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA/25, or PTO/AIA/26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer. 08-34 AIA Claim s 1-6, 11, 15 and 19 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim s 1, 3, 5-9, 14-15, 17 and 19 of U.S. Patent No. 12,342,990 . Although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of present Application ‘923 is similar to the combination of claims 1, 3 and 5 of Patent ‘990. Thus, claim 1 of present Application ‘923 is anticipated by the combination of claims 1, 3 and 5 of Patent ‘990. Peruse the table below . Claim 2 of present Application ‘923 is similar to claim 7 of Patent ‘990. Thus, claim 2 of present Application ‘923 is anticipated by claim 7 of Patent ‘990. Claim 3 of present Application ‘923 is similar to claim 8 of Patent ‘990. Thus, claim 3 of present Application ‘923 is anticipated by claim 8 of Patent ‘990. Claim 4 of present Application ‘923 is similar to claim 9 of Patent ‘990. Thus, claim 4 of present Application ‘923 is anticipated by claim 9 of Patent ‘990. Claim 5 of present Application ‘923 is similar to the combination of claims 5 and 6 of Patent ‘990. Thus, claim 5 of present Application ‘923 is anticipated by the combination of claims 5 and 6 of Patent ‘990. Claim 6 of present Application ‘923 is similar to claim 5 of Patent ‘990. Thus, claim 6 of present Application ‘923 is anticipated by claim 5 of Patent ‘990. Claim 11 of present Application ‘923 is similar to claim 1 of Patent ‘990. Thus, claim 11 of present Application ‘923 is anticipated by claim 1 of Patent ‘990. Claim 15 of present Application ‘923 is similar to the combination of claims 14 and 15 of Patent ‘990. Thus, claim 15 of present Application ‘923 is anticipated by the combination of claims 14 and 15 of Patent ‘990. Claim 19 of present Application ‘923 is similar to the combination of claims 17 and 19 of Patent ‘990. Thus, claim 19 of present Application ‘923 is anticipated by the combination of claims 17 and 19 of Patent ‘990. Peruse the table below. Present Application 19/231,923 US Patent No. 12,342,990 Claim 1. A system comprising: an illumination device configured to sequentially illuminate a surface in a plurality of colors; a monochromatic image sensor configured to capture a plurality of image frames of the surface as the surface is sequentially illuminated in the plurality of colors by the illumination device; and a computing device including at least one memory storing instructions, and at least one processor coupled to the at least one memory for executing the instructions to perform operations, the operations including: receiving the plurality of image frames from the monochromatic image sensor, each of the plurality of image frames comprising a plurality of pixels; identifying, in each of the plurality of image frames, a pixel block comprising a subset of the plurality of pixels associated with a target feature; generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels within the pixel block identified in each of the plurality of image frames; and generating, based on the plurality of pixel intensity maps, relative pixel blocks across the plurality of image frames, the relative pixel blocks representing the target feature in the plurality of image frames. Claim 1. A system comprising: an illumination device configured to sequentially illuminate a surface in a plurality of colors; a monochromatic image sensor configured to capture a plurality of image frames of the surface as the surface is sequentially illuminated in the plurality of colors by the illumination device; and a computing device including at least one memory storing instructions, and at least one processor coupled to the at least one memory for executing the instructions to perform operations, the operations including: receiving the plurality of image frames from the monochromatic image sensor; identifying a target in the plurality of image frames, wherein the target is positioned at a different location in each of the plurality of image frames indicative of a motion of the target; generating a plurality of intensity relationship maps of the target corresponding to the plurality of image frames; and determining the motion of the target between the plurality of image frames based on the plurality of intensity relationship maps of the target. Claim 3. The system of claim 1, wherein determining the motion of the target comprises: identifying a matching subset of pixels across the plurality of intensity relationship maps; and determining the motion of the target between the plurality of image frames by comparing the matching subset of pixels across the plurality of intensity relationship maps. Claim 5. The system of claim 3, wherein identifying the matching subset of pixels comprises: generating correlation scores for a plurality of subsets of pixels across the plurality of intensity relationship maps of the target; and identifying the matching subset of pixels, from the plurality of subsets of pixels, based on a correlation score for the matching subset of pixels being above a predefined threshold value. Claim 2. The system of claim 1, wherein generating the plurality of pixel intensity maps includes: for the pixel block identified in each of the plurality of image frames, performing edge detection filtering on the pixel block to generate an edge converted pixel block; and generating a corresponding pixel intensity map, of the plurality of pixel intensity maps, for each frame based on pixel intensity data of the edge converted pixel block. Claim 7. The system of claim 1, wherein generating the plurality of intensity relationship maps of the target comprises: applying edge detection filtering to a subset of pixels associated with the target to extract a correlation feature of the target from each of the plurality of image frames; and generating the plurality of intensity relationship maps of the target for the correlation feature of the target extracted from each of the plurality of image frames. Claim 3. The system of claim 1, wherein the operations further include: normalizing the pixel intensity values of the plurality of image frames prior to generating the plurality of pixel intensity maps. Claim 8. The system of claim 1, the operations further including: normalizing color intensities of the plurality of image frames. Claim 4. The system of claim 3, wherein normalizing the pixel intensity values of the plurality of image frames includes: determining an intensity of each color of the plurality of colors in a respective image frame of the plurality of image frames captured as the surface is illuminated with the respective color by the illumination device; and assigning a normalization value to the determined intensity of the respective color. Claim 9. The system of claim 8, wherein normalizing the color intensities of the plurality of image frames comprises: determining an intensity of each color of the plurality of colors when the surface is illuminated with the respective color by the illumination device; and assigning a normalization value to the determined intensity of the respective color. Claim 5. The system of claim 1, wherein generating, based on the plurality of pixel intensity maps, the relative pixel blocks across the plurality of image frames includes: determining a correlation score for an intensity distribution peak in each of the plurality of pixel intensity maps that correspond to the plurality of image frames; and identifying one or more matching pixels, from the subset of the plurality of pixels and corresponding to the intensity distribution peak, in each of the plurality of image frames based on the correlation score across the plurality of pixel intensity maps, wherein the one or more matching pixels in each of the plurality of image frames form the relative pixel blocks. Claim 5. The system of claim 3, wherein identifying the matching subset of pixels comprises: generating correlation scores for a plurality of subsets of pixels across the plurality of intensity relationship maps of the target; and identifying the matching subset of pixels, from the plurality of subsets of pixels, based on a correlation score for the matching subset of pixels being above a predefined threshold value. Claim 6. The system of claim 3, wherein identifying the matching subset of pixels comprises: generating a plurality of pixel projection data sets based on the plurality of intensity relationship maps of the target; and identifying, among the plurality of pixel projection data sets, the matching subset of pixels by determining peak intensity clusters in the plurality of pixel projection data sets, the peak intensity clusters corresponding to the matching subset of pixels. Claim 6. The system of claim 5, wherein identifying the one or more matching pixels further includes identifying the one or more matching pixels based on the correlation score across the plurality of pixel intensity maps exceeding a predetermined threshold correlation score. Claim 5. The system of claim 3, wherein identifying the matching subset of pixels comprises: generating correlation scores for a plurality of subsets of pixels across the plurality of intensity relationship maps of the target; and identifying the matching subset of pixels, from the plurality of subsets of pixels, based on a correlation score for the matching subset of pixels being above a predefined threshold value. Claim 11. The system of claim 1, wherein the target feature is positioned at a different location in each of the plurality of image frames, indicative of motion between the plurality of image frames, and the operations further include determining the motion based on a comparing of the relative pixel blocks. Claim 1. A system comprising: an illumination device configured to sequentially illuminate a surface in a plurality of colors; a monochromatic image sensor configured to capture a plurality of image frames of the surface as the surface is sequentially illuminated in the plurality of colors by the illumination device; and a computing device including at least one memory storing instructions, and at least one processor coupled to the at least one memory for executing the instructions to perform operations, the operations including: receiving the plurality of image frames from the monochromatic image sensor; identifying a target in the plurality of image frames, wherein the target is positioned at a different location in each of the plurality of image frames indicative of a motion of the target; generating a plurality of intensity relationship maps of the target corresponding to the plurality of image frames; and determining the motion of the target between the plurality of image frames based on the plurality of intensity relationship maps of the target. Claim 15. A computing device comprising: at least one memory storing instructions; and at least one processor coupled to the at least one memory for executing the instructions to perform operations, the operations including: receiving, from a monochromatic image sensor, a plurality of image frames of a surface captured by the monochromatic image sensor as the surface is sequentially illuminated in a plurality of colors by an illumination device, each of the plurality of image frames comprising a plurality of pixels; identifying, in each of the plurality of image frames, a subset of the plurality of pixels including a target feature; generating a plurality of pixel intensity maps that correspond to the plurality of image frames based on pixel intensity values for the subset of the plurality of pixels in each of the plurality of image frames; and identifying, based on a comparing of the plurality of pixel intensity maps, one or more matching pixels across each of the plurality of image frames, the one or more matching pixels representing the target feature in each of the plurality of image frames. Claim 14. A computing device comprising: at least one memory storing instructions; and at least one processor coupled to the at least one memory for executing the instructions to perform operations, the operations including: receiving, from a monochromatic image sensor, a plurality of image frames of a surface captured by the monochromatic image sensor as the surface is sequentially illuminated in a plurality of colors by an illumination device; identifying a target in the plurality of image frames, wherein the target is positioned at a different location in each of the plurality of image frames indicative of a motion of the target; generating a plurality of intensity relationship maps of the target corresponding to the plurality of image frames; and determining the motion of the target between the plurality of image frames based on the plurality of intensity relationship maps of the target. Claim 15. The computing device of claim 14, wherein determining the motion of the target comprises: identifying a matching subset of pixels across the plurality of intensity relationship maps; and determining the motion of the target between the plurality of image frames by comparing the matching subset of pixels across the plurality of intensity relationship maps. Claim 19. A computer-implemented method comprising: receiving, from a monochromatic image sensor, a first image frame and a second image frame of multimodal spectrum captured by the monochromatic image sensor, each of the first image frame and the second image frame comprising a plurality of pixels; identifying a first pixel block in the first image frame and a second pixel block in the second image frame, each of the first pixel block and the second pixel block comprising a subset of the plurality of pixels associated with a target feature in the first image frame or the second image frame, respectively; generating a first pixel intensity map based on first pixel intensity data of the first pixel block; generating a second pixel intensity map based on second pixel intensity data of the second pixel block; and identifying, based on a comparing of the first pixel intensity map and the second pixel intensity map, one or more matching pixels across the first pixel block and the second pixel block, the one or more matching pixels representing the target feature in each of the first image frame and the second image frame. Claim 17. A computer-implemented method comprising: receiving, from a monochromatic image sensor, a plurality of image frames of a surface captured by the monochromatic image sensor as the surface is sequentially illuminated in a plurality of colors by an illumination device; identifying a target in the plurality of image frames, wherein the target is positioned at a different location in each of the plurality of image frames indicative of a motion of the target; generating a plurality of intensity relationship maps of the target corresponding to the plurality of image frames; identifying a matching subset of pixels across the plurality of intensity relationship maps; and determining the motion of the target between the plurality of image frames by comparing the matching subset of pixels across the plurality of intensity relationship maps. Claim 19. The method of claim 17, wherein identifying the matching subset of pixels comprises: generating correlation scores for a plurality of subsets of pixels across the plurality of image frames; and determining the matching subset of pixels, from the plurality of subsets of pixels, based on a correlation score for the matching subset of pixels being above a predefined threshold value . Allowable Subject Matter 12-151-08 AIA 07-43 12-51-08 Claim s 7-9 and 17 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. Contact Information Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALLEN C WONG whose telephone number is (571)272-7341. The examiner can normally be reached on Flex Monday-Thursday 9:30am-7:30pm. 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If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ALLEN C WONG/Primary Examiner, Art Unit 2488 Application/Control Number: 19/231,923 Page 2 Art Unit: 2488 Application/Control Number: 19/231,923 Page 3 Art Unit: 2488 Application/Control Number: 19/231,923 Page 4 Art Unit: 2488 Application/Control Number: 19/231,923 Page 5 Art Unit: 2488 Application/Control Number: 19/231,923 Page 6 Art Unit: 2488 Application/Control Number: 19/231,923 Page 7 Art Unit: 2488 Application/Control Number: 19/231,923 Page 8 Art Unit: 2488 Application/Control Number: 19/231,923 Page 9 Art Unit: 2488 Application/Control Number: 19/231,923 Page 10 Art Unit: 2488 Application/Control Number: 19/231,923 Page 11 Art Unit: 2488 Application/Control Number: 19/231,923 Page 12 Art Unit: 2488 Application/Control Number: 19/231,923 Page 13 Art Unit: 2488 Application/Control Number: 19/231,923 Page 14 Art Unit: 2488 Application/Control Number: 19/231,923 Page 15 Art Unit: 2488 Application/Control Number: 19/231,923 Page 16 Art Unit: 2488 Application/Control Number: 19/231,923 Page 17 Art Unit: 2488 Application/Control Number: 19/231,923 Page 18 Art Unit: 2488 Application/Control Number: 19/231,923 Page 19 Art Unit: 2488 Application/Control Number: 19/231,923 Page 20 Art Unit: 2488 Application/Control Number: 19/231,923 Page 21 Art Unit: 2488 Application/Control Number: 19/231,923 Page 22 Art Unit: 2488 Application/Control Number: 19/231,923 Page 23 Art Unit: 2488 Application/Control Number: 19/231,923 Page 24 Art Unit: 2488 Application/Control Number: 19/231,923 Page 25 Art Unit: 2488 Application/Control Number: 19/231,923 Page 26 Art Unit: 2488 Application/Control Number: 19/231,923 Page 27 Art Unit: 2488 Application/Control Number: 19/231,923 Page 28 Art Unit: 2488 Application/Control Number: 19/231,923 Page 29 Art Unit: 2488 Application/Control Number: 19/231,923 Page 30 Art Unit: 2488 Application/Control Number: 19/231,923 Page 31 Art Unit: 2488
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