Abstract

A system and method for detection of gas in the atmosphere from a multispectral image including a plurality of pixels, each pixel having a spectral signature including a set of intensities of electromagnetic (EM) energy reflected at various bands, the method including: clustering the plurality of pixels based on channels of the spectral signatures that are indicative of presence of the gas, to produce a first set of clusters; clustering the plurality of pixels based on channels of the spectral signatures that are non -indicative of presence of the gas, to produce a second set of clusters; matching clusters from the first set of clusters and the second set of clusters; and labeling clusters that are present in the first set of clusters and not present in the second set of clusters as suspected as including the gas.

IPC Classes  ?

• G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
• G06V 10/58 - Extraction of image or video features relating to hyperspectral data
• G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
• G06V 20/10 - Terrestrial scenes

Abstract

A system and method for detection of gas in the atmosphere from a multispectral image including a plurality of pixels, each pixel having a spectral signature including a set of intensities of electromagnetic (EM) energy reflected at various bands, the method including: clustering the plurality of pixels based on channels of the spectral signatures that are indicative of presence of the gas, to produce a first set of clusters; clustering the plurality of pixels based on channels of the spectral signatures that are non-indicative of presence of the gas, to produce a second set of clusters; matching clusters from the first set of clusters and the second set of clusters; and labeling clusters that are present in the first set of clusters and not present in the second set of clusters as suspected as including the gas.

IPC Classes  ?

• G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
• G06V 10/58 - Extraction of image or video features relating to hyperspectral data
• G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
• G06V 20/10 - Terrestrial scenes

Abstract

A system and method for detection of gas in the atmosphere front a multispectral image including a plurality of pixels, each pixel having a spectral signature including a set of intensities of electromagnetic (EM) energy reflected at various bands, the method including: clustering the plurality of pixels based on channels of the spectral signatures that are indicative of presence of the gas, to produce a first set of clusters; clustering the plurality of pixels based on channels of the spectral signatures that are non-indicative of presence of the gas, to produce a second set of clusters; matching clusters from the first set of clusters and the second set of clusters; and labeling clusters that are present in the first set of clusters and not present in the second set of clusters as suspected as including the gas.

IPC Classes  ?

• G06V 10/762 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using clustering, e.g. of similar faces in social networks
• G06V 10/58 - Extraction of image or video features relating to hyperspectral data
• G06V 10/75 - Organisation of the matching processes, e.g. simultaneous or sequential comparisons of image or video featuresCoarse-fine approaches, e.g. multi-scale approachesImage or video pattern matchingProximity measures in feature spaces using context analysisSelection of dictionaries
• G06V 20/10 - Terrestrial scenes
• G06V 20/52 - Surveillance or monitoring of activities, e.g. for recognising suspicious objects

Abstract

A system and method for encoding a digital image may include obtaining image data of the digital image, wherein the image data comprises a plurality of image pixels, selecting a plurality of sample pixels from the plurality of image pixels, clustering the plurality of sample pixels based on an influence function to generate a plurality of hue clusters, classifying the image pixels to the plurality of the hue clusters, and assigning hue values of the hue clusters to the plurality of the image pixels.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• G06T 7/90 - Determination of colour characteristics
• H04N 9/67 - Circuits for processing colour signals for matrixing

Abstract

A system and method for encoding a digital image may include obtaining image data of the digital image, wherein the image data comprises a plurality of image pixels, selecting a plurality of sample pixels from the plurality of image pixels, clustering the plurality of sample pixels based on an influence function to generate a plurality of hue clusters, classifying the image pixels to the plurality of the hue clusters, and assigning hue values of the hue clusters to the plurality of the image pixels.

IPC Classes  ?

• G06T 5/00 - Image enhancement or restoration
• G06T 5/40 - Image enhancement or restoration using histogram techniques
• G06T 7/10 - SegmentationEdge detection
• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints

Abstract

A system and method for encoding a digital image may include obtaining image data of the digital image, wherein the image data comprises a plurality of image pixels, selecting a plurality of sample pixels from the plurality of image pixels, clustering the plurality of sample pixels based on an influence function to generate a plurality of hue clusters, classifying the image pixels to the plurality of the hue clusters, and assigning hue values of the hue clusters to the plurality of the image pixels.

IPC Classes  ?

• G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
• G06T 7/90 - Determination of colour characteristics
• H04N 9/67 - Circuits for processing colour signals for matrixing

Abstract

A system and method for selecting a subset of images may include: obtaining a plurality of image files, each image file relating to a digital image of the plurality of digital images, each file including image data and metadata, the metadata including a first set of features, and a second set of features; clustering the plurality of images based on at least one of the first set of features to generate clusters of images; selecting a set of M largest clusters of images, wherein M is a positive integer; scoring the images of each of the selected clusters based on at least one of the second set of features; and selecting a set of N images with a highest score from the selected clusters, wherein N is a positive integer.

IPC Classes  ?

• G06F 16/55 - ClusteringClassification
• G06F 16/538 - Presentation of query results
• G06F 16/535 - Filtering based on additional data, e.g. user or group profiles
• G06F 16/58 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually