# US 2013/0156307 A1 · Systems and methods for efficiently and accurately detecting changes in spatial feature data > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2013/0156307 A1 - Document ID: US20130156307A1 - Status: Published application - Kind: A1 - Application number: 13/328,031 - Filed: 2011-12-16 - Published: 2013-06-20 - Earliest claimed: 2011-12-16 - Assignees: Harris Corporation - Inventors: J. Harlan Yates; Michael McGonagle; Robert Haden; Mark Rahmes - Web page: https://patentgrep.com/patent/US20130156307A1 ## CPC - G06T 7/246: using feature-based methods, e.g. the tracking of corners or segments - G06F 18/2433: Single-class perspective, e.g. one-against-all classification; Novelty detection; Outlier detection - G06F 18/40: Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor - G06T 7/254: involving subtraction of images - G06V 10/143: Sensing or illuminating at different wavelengths - G06V 10/757: {Matching configurations of points or features} - G06V 10/764: using classification, e.g. of video objects - G06V 10/945: {User interactive design; Environments; Toolboxes} - G06T 2200/24: involving graphical user interfaces [GUIs] - G06T 2207/10016: Video; Image sequence - G06T 2207/10024: Color image - G06T 2207/10032: Satellite or aerial image; Remote sensing - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING ## Abstract Systems (100) and methods (300) for efficiently and accurately detecting changes in feature data. The methods generally involve: determining first vectors for first features extracted from a first image using pixel information associated therewith; comparing the first vectors with second vectors defined by spatial feature data; classifying the first features into a plurality of classes based on the results of the vector comparisons; and analyzing the first image to determine if any one of the first features of at least one of the plurality of classes indicates that a relevant change has occurred in relation to an object represented thereby. ## Claims ### Claim 1 A method for efficiently and accurately detecting changes in feature data, comprising: determining, by at least one electronic circuit, first vectors for first features extracted from a first image; comparing, by the electronic circuit, the first vectors with pre-defined second vectors; classifying, by the electronic circuit, the first features into a plurality of classes based on the results of the comparing step; and analyzing the first image to determine if any one of the first features of at least one of the plurality of classes indicates that a relevant change has occurred in relation to an object represented thereby. ### Claim 2 (depends on 1) The method according to claim 1, wherein the first vectors are determined by converting locations of pixels defining the first features to coordinates of a multi-dimensional space. ### Claim 3 (depends on 1) The method according to claim 1, wherein the first vectors and the second vectors are compared with each other to determine mathematically which of the first features overlap one or more of second features. ### Claim 4 (depends on 3) The method according to claim 3, wherein the first features which overlap the second features are classified as “matched features”. ### Claim 5 (depends on 3) The method according to claim 3, wherein the first features which do not overlap any of the second features are classified as “new features”. ### Claim 6 (depends on 3) The method according to claim 3, wherein the second features which do not have any overlapping first features are classified as “deleted features”. ### Claim 7 (depends on 1) The method according to claim 1, further comprising determining, by the electronic circuit, a plurality of confidence values indicating a degree of similarity, difference or overlap between the first features and pre-defined second features. ### Claim 8 (depends on 1) The method according to claim 1, wherein the analyzing step comprises: automatically and simultaneously generating a plurality of chip images for the first image, the chip images comprising panned and/or zoomed views of the first image of objects defined by a user-selected feature and other features of the same feature class as the user-selected feature; and analyzing the plurality of chip images to determine if any one of the first features indicates that a relevant change has occurred in relation to the object represented thereby. ### Claim 9 (depends on 1) The method according to claim 1, wherein the analyzing step comprises comparing the contents of the first image with the contents of a second image to determine if any one of the first features indicates that a relevant change has occurred in relation to the object represented thereby. ### Claim 10 (depends on 1) The method according to claim 1, wherein the analyzing step comprises: generating at least one color difference image using imagery data for the first image and imagery data for a second image; and analyzing the color difference image to determine if any one of the features thereof indicates that a relevant change has occurred in relation to the object represented thereby. ### Claim 11 A system, comprising: at least one electronic circuit configured to determine first vectors for first features extracted from a first image, compare the first vectors with pre-defined second vectors, classify the first features into a plurality of classes based on the results of the comparing step, and analyze the first image to determine if any one of the first features of at least one of the plurality of classes indicates that a relevant change has occurred in relation to an object represented thereby. ### Claim 12 (depends on 11) The system according to claim 11, wherein the first vectors are determined by converting locations of pixels defining the first features to coordinates of a multi-dimensional space. ### Claim 13 (depends on 11) The system according to claim 11, wherein the first vectors and the second vectors are compared with each other to determine mathematically which of the first features overlap one or more second features defined by previously stored data. ### Claim 14 (depends on 13) The system according to claim 13, wherein the first features which overlap the second features are classified as “matched features”. ### Claim 15 (depends on 13) The system according to claim 13, wherein the first features which do not overlap any of the second features are classified as “new features”. ### Claim 16 (depends on 13) The system according to claim 13, wherein the second features which do not have any overlapping first features are classified as “deleted features”. ### Claim 17 (depends on 11) The system according to claim 11, wherein the electronic circuit is further configured to determine a plurality of confidence values indicating a degree of similarity, difference or overlap between the first features and second features defined by previously stored data. ### Claim 18 (depends on 11) The system according to claim 11, wherein the electronic circuit is further configured to automatically and simultaneously generate a plurality of chip images for the first image, the chip images comprising panned and/or zoomed views of the first image of objects defined by a user-selected feature and other features of the same feature class as the user-selected feature, and facilitate a user analysis of the plurality of chip images to identify at least one first feature which indicates that a relevant change has occurred in relation to the object represented thereby. ### Claim 19 (depends on 11) The system according to claim 11, wherein the electronic circuit is further configured to facilitate a user comparison of the contents of the first image with the contents of a second image to identify at least one first feature which indicates that a relevant change has occurred in relation to the object represented thereby. ### Claim 20 (depends on 11) The system according to claim 11, wherein the electronic circuit is further configured to generate at least one color difference image using imagery data for the first image and imagery data for a second image, and facilitate a user analysis of the color difference image to identify at least one feature thereof which indicates that a relevant change has occurred in relation to the object represented thereby.