# US 10,311,098 B2 · System and method for storing points of polygons related to an image > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,311,098 B2 - Document ID: US10311098B2 - Status: Granted - Kind: B2 - Application number: 16/032,401 - Filed: 2018-07-11 - Published: 2018-11-08 - Granted: 2019-06-04 - Earliest claimed: 2010-03-16 - Assignees: Pixia Corp. - Applicants: Pixia Corp. - Inventors: Rahul C. Thakkar - Web page: https://patentgrep.com/patent/US10311098B2 ## CPC - G06F 16/5838: {using colour} - G06F 16/2246: {Trees, e.g. B+trees} - G06F 16/282: {Hierarchical databases, e.g. IMS, LDAP data stores or Lotus Notes} - G06F 16/51: Indexing; Data structures therefor; Storage structures - G06F 16/5854: {using shape and object relationship} - G06T 7/00: Image analysis - G06T 7/0002: {Inspection of images, e.g. flaw detection} - G06T 7/11: Region-based segmentation - G06T 7/13: Edge detection - G06T 7/50: Depth or shape recovery - G06T 7/60: Analysis of geometric attributes - G06T 7/90: Determination of colour characteristics - H04N 19/182: the unit being a pixel - H04N 19/184: the unit being bits, e.g. of the compressed video stream - H04N 19/186: the unit being a colour or a chrominance component - H04N 19/40: using video transcoding, i.e. partial or full decoding of a coded input stream followed by re-encoding of the decoded output stream - G06T 2207/20021: Dividing image into blocks, subimages or windows - G06T 2207/20112: Image segmentation details - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract A system and method for storing data may include: unevenly dividing the image into polygonal image sections having pixels with band(s) and a bit depth per band that is too high for displaying on a display screen, dividing the image into quads such that each quad has a boundary that contains a portion of one of the polygonal image sections, obtaining statistical data computed for each of the bands of each of the pixels within each of the polygonal image sections, storing, with respect to a reduced resolution dataset (R-Set) of the image, coordinates of bounds of a polygonal image section that intersects with a quad, organizing the image, the quads, and the polygonal image sections in a tree structure, and storing the statistical data, the pixel coordinates, and the tree structure. ## Claims ### Claim 1 The following listing of claims replaces all prior listings: A method for storing data related to an image, the method being implemented by a computer system that includes one or more processors configured to execute computer program instructions, the method comprising: unevenly dividing the image into a plurality of polygonal image sections each comprising a plurality of pixels, wherein each of the pixels has one or more bands and a bit depth per band that is too high for displaying on a display screen; dividing the image into a plurality of quads such that each quad has a boundary that contains at least a portion of one of the plurality of polygonal image sections; obtaining statistical data associated with the image, the statistical data being computed for each of the bands of each of the pixels within each of the polygonal image sections; storing, with respect to a reduced resolution dataset (R-Set) of the image, pixel coordinates of bounds of at least one polygonal image section that intersects with a quad; organizing the image, the plurality of quads, and the plurality of polygonal image sections in a tree structure; and storing the statistical data, the pixel coordinates, and the tree structure. ### Claim 2 (depends on 1) The method according to claim 1, wherein the uneven division into the plurality of polygonal image sections results in at least two polygonal image sections of the plurality of polygonal image sections that have different polygonal shapes, area sizes, or numbers of sides, and wherein each of the plurality of quads is rectangular. ### Claim 3 (depends on 1) The method according to claim 1, further comprising: storing a plurality of reduced resolution datasets (R-Sets), each of the R-Sets being a progressively smaller version of the image, wherein data describing each of the polygonal image sections is stored with the statistical data for pixels within the each section. ### Claim 4 (depends on 1) The method according to claim 1, further comprising: determining in which quad of the plurality of quads and, for each quad, in which of the plurality of polygonal image sections each pixel is located by traversing the tree structure from a root node corresponding to the image to leaf nodes corresponding to the polygonal image sections, wherein the tree structure is traversed sequentially. ### Claim 5 (depends on 1) The method according to claim 1, further comprising: determining in which quad of the plurality of quads and, for each quad, in which of the plurality of polygonal image sections each pixel is located by traversing the tree structure from a root node corresponding to the image to leaf nodes corresponding to the polygonal image sections, wherein the tree structure is traversed using parallel processing. ### Claim 6 (depends on 1) The method according to claim 1, wherein the statistical data of each band of each pixel within each of the polygonal image sections of the image comprises a histogram, and wherein if a pixel is within multiple, overlapping polygonal image sections then the most recently computed histogram of the overlapping polygonal image section is used in computing the statistical data. ### Claim 7 (depends on 1) The method according to claim 1, further comprising: converting each pixel having the bit depth per band that is too high for displaying on the display screen in an area of interest of the image into a corresponding pixel that has a lower bit depth per band displayable on the display screen using the statistical data of each of the polygonal image sections in which the respective pixel is located to obtain an image that corresponds to the area of interest and that has pixels with the lower bit depth per band. ### Claim 8 (depends on 1) The method according to claim 1, wherein the statistical data for pixels within each of the polygonal image sections is used to generate a plurality of look up tables, each look up table in the plurality of look up tables being associated with the corresponding polygonal image section of the plurality of polygonal image sections. ### Claim 9 (depends on 1) The method according to claim 1, wherein the statistical data for pixels within each of the polygonal image sections are computed using one or more of standard deviation, minimum/maximum values, mean, median, mode, skew, and kurtosis for each band of each pixel in the image. ### Claim 10 (depends on 2) The method according to claim 2, wherein each of the at least two polygonal image sections has substantially homogenous features that differ from one another. ### Claim 11 A computer system for storing data related to an image, the image being associated with statistical data, the computer system comprising one or more processors configured to: unevenly divide the image into a plurality of polygonal image sections each comprising a plurality of pixels, wherein each of the pixels has one or more bands and a bit depth per band that is too high for displaying on a display screen; divide the image into a plurality of quads such that each quad has a boundary that contains at least a portion of one of the plurality of polygonal image sections; obtain statistical data associated with the image, the statistical data being computed for each of the bands of each of the pixels within each of the polygonal image sections; store, with respect to a reduced resolution dataset (R-Set) of the image, pixel coordinates of bounds of at least one polygonal image section that intersects with a quad; organize the image, the plurality of quads, and the plurality of polygonal image sections in a tree structure; and store the statistical data, the pixel coordinates, and the tree structure. ### Claim 12 (depends on 11) The computer system according to claim 11, wherein the uneven division into the plurality of polygonal image sections comprises at least two polygonal image sections of the plurality of polygonal image sections that have different polygonal shapes or area sizes or that have a different number of sides, and wherein each of the plurality of quads is rectangular. ### Claim 13 (depends on 11) The computer system according to claim 11, wherein the one or more processors are further configured to store a plurality of reduced resolution datasets (R-Sets), each of the R-Sets being a progressively smaller version of the image, and wherein data describing each of the polygonal image sections is stored with the statistical data for pixels within the each section. ### Claim 14 (depends on 11) The computer system according to claim 11, wherein the one or more processors are further configured to: determine in which quad of the plurality of quads and, for each quad, in which of the plurality of polygonal image sections each pixel is located by traversing the tree structure from a root node corresponding to the image to leaf nodes corresponding to the polygonal image sections, wherein the tree structure is traversed sequentially. ### Claim 15 (depends on 11) The computer system according to claim 11, wherein the one or more processors are further configured to: determine in which quad of the plurality of quads and, for each quad, in which of the plurality of polygonal image sections each pixel is located by traversing the tree structure from a root node corresponding to the image to leaf nodes corresponding to the polygonal image sections, wherein the tree structure is traversed using parallel processing. ### Claim 16 (depends on 11) The computer system according to claim 11, wherein the statistical data of each band of each pixel within each of the polygonal image sections of the image comprises a histogram, wherein if a pixel is within multiple, overlapping polygonal image sections then the most recently computed histogram of the overlapping polygonal image section is used in computing the statistical data. ### Claim 17 (depends on 11) The computer system according to claim 11, wherein the one or more processors are further configured to convert each pixel having the bit depth per band that is too high for displaying on the display screen in an area of interest of the image into a corresponding pixel that has a lower bit depth per band displayable on the display screen using the statistical data of each of the polygonal image sections in which the respective pixel is located to obtain an image that corresponds to the area of interest and that has pixels with the lower bit depth per band. ### Claim 18 (depends on 11) The computer system according to claim 11, wherein the statistical data for pixels within each of the polygonal image sections is used to generate a plurality of look up tables, each look up table in the plurality of look up tables being associated with the corresponding polygonal image section of the plurality of polygonal image sections. ### Claim 19 (depends on 11) The computer system according to claim 11, wherein the statistical data for pixels within each of the polygonal image sections are computed using one or more of standard deviation, minimum/maximum values, mean, median, mode, skew, and kurtosis for each band of each pixel in the image. ### Claim 20 (depends on 12) The computer system according to claim 12, wherein each of the at least two polygonal image sections has substantially homogenous features that differ from one another.