# US 2014/0153779 A1 · Object Segmentation at a Self-Checkout > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2014/0153779 A1 - Document ID: US20140153779A1 - Status: Published application - Kind: A1 - Application number: 14/175,335 - Filed: 2014-02-07 - Published: 2014-06-05 - Earliest claimed: 2010-07-27 - Assignees: International Business Machines Corporation - Applicants: International Business Machines Corporation - Inventors: Rogerio S. Feris; Charles A. Otto; Sharathchandra Pankanti; Duan D. Tran - Web page: https://patentgrep.com/patent/US20140153779A1 ## CPC - G06T 7/11: Region-based segmentation - G06T 7/136: involving thresholding - G06T 2207/10024: Color image - G06T 2207/20012: Locally adaptive - G06T 2207/20021: Dividing image into blocks, subimages or windows - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract Techniques for segmenting an object are provided. The techniques include capturing an image of an object, dividing the image into one or more blocks, computing a confidence value for each of the one or more blocks, and eliminating one or more blocks from consideration based on the confidence value for each of the one or more blocks. ## Claims ### Claim 1 A method comprising: capturing an image of an object; dividing the image into one or more blocks; computing a confidence value for each of the one or more blocks; and eliminating one or more blocks from consideration based on the confidence value for each of the one or more blocks. ### Claim 2 (depends on 1) The method of claim 1, further comprising: reading a barcode for the object; and using a database to identify one or more known features corresponding to the barcode. ### Claim 3 (depends on 2) The method of claim 2, further comprising comparing the one or more computed features of the image with the one or more known features corresponding to the barcode to determine whether or not the image matches the object's barcode identity. ### Claim 4 (depends on 1) The method of claim 1, further comprising creating and maintaining a set of one or more reference background images. ### Claim 5 (depends on 4) The method of claim 4, wherein the set of one or more background reference images cover one or more visual variations of a self-checkout. ### Claim 6 (depends on 4) The method of claim 4, wherein creating and maintaining a set of one or more reference background images comprises creating and maintaining a set of one or more reference background images over two or more different time periods. ### Claim 7 (depends on 4) The method of claim 4, further comprising dividing each reference background image into a set of one or more non-overlapping blocks. ### Claim 8 (depends on 7) The method of claim 7, further comprising extracting one or more features from each of the one or more non-overlapping blocks. ### Claim 9 (depends on 1) The method of claim 1, further comprising using the confidence value of each block to weight a color histogram used for object classification. ### Claim 10 (depends on 1) The method of claim 1, wherein said capturing comprises capturing, via a camera, an image of an object as it moves across an open conveyor belt of a self-checkout. ### Claim 11 (depends on 1) The method of claim 1, wherein said eliminating comprises eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks. ### Claim 12 (depends on 11) The method of claim 11, wherein eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks comprises iteratively eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks. ### Claim 13 (depends on 1) The method of claim 1, further comprising computing one or more features of the image. ### Claim 14 (depends on 1) The method of claim 1, wherein said computing a confidence value fix each of the one or more blocks comprises using a minimum feature distance from one or more reference background blocks. ### Claim 15 A computer program product comprising a tangible computer readable recordable storage device including computer useable program code, the computer program product including: computer useable program code for capturing an image of an object; computer useable program code for dividing the image into one or more blocks; computer useable program code for computing a confidence value for each of the one or more blocks; and computer useable program code for eliminating one or more blocks from consideration based on the confidence value for each of the one or more blocks. ### Claim 16 (depends on 15) The computer program product of claim 15, further comprising: computer useable program code for reading a barcode for the object at a self-checkout; and computer useable program code for using a database to identify one or more known features corresponding to the barcode. ### Claim 17 (depends on 15) The computer program product of claim 15, further comprising computer useable program code for creating and maintaining a set of one or more reference background images. ### Claim 18 (depends on 15) The computer program product of claim 15, wherein said eliminating comprises eliminating one or more blocks from consideration via use of an adaptive threshold computed on the confidence value for each of the one or more blocks. ### Claim 19 (depends on 15) The computer program product of claim 15, wherein said computing a confidence value for each of the one or more blocks comprises using a minimum feature distance from one or more reference background blocks. ### Claim 20 A system comprising: a memory; and at least one processor coupled to the memory and operative to: capture an image of an object; divide the image into one or more blocks; compute a confidence value for each of the one or more blocks; and eliminate one or more blocks from consideration based on the confidence value for each of the one or more blocks.