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US 9,805,280 B2Granted
Image analysis systems and methods
AssigneeNetspark Ltd.
InventorsElyasaf Korenwaitz, Haim Eaoshyhes
Life of this patent
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Abstract
A system including: (a) a network hub or port adapted to detect image files in transit according to their file designations; (b) an object detector configured to identify one or more regions of interest (ROI) in each image file as potentially containing an object of interest (OOI); (c) a feature analyzer adapted to express one or more General Classification Features (GCF) of each ROI as a vector; and (d) a decision module adapted accept or reject each ROI as containing said OOI based upon the one or more GCF vectors.
Claims11
A system comprising:
- (a) a network hub or port adapted to detect image files in transit according to their file designations;
- (b) an object detector configured to identify one or more regions of interest (ROI) in each image file as potentially containing an object of interest (OOI);
- (c) a feature analyzer adapted to express one or more General Classification Features (GCF) of each ROI as a vector;
- and
- (d) a decision module adapted accept or reject each ROI as containing said OOI based upon said one or more GCF vectors, wherein said GCFs include one or more of Gabor function, skin blob geometric and color information, intensity edge histogram, 3 colors plane edge histogram, color information such as color histogram, color layout, color moment, color structure and scalable color.
2 more elements
A system comprising:
- (a) a network hub or port adapted to detect image files in transit according to their file designations;
- (b) an object detector configured to identify one or more regions of interest (ROI) in each image file as potentially containing an object of interest (OOI);
- (c) a feature analyzer adapted to express one or more General Classification Features (GCF) of each ROI as a vector;
- and
- (d) a decision module adapted accept or reject each ROI as containing said OOI based upon said one or more GCF vectors, wherein a formula is used to summarize two or more GCFs and/or the global probability vector.
2 more elements
Dependencies are inferred from the claim text.