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Feature-based detection and context discriminate classification for digital images
Feature-based detection and context discriminate classification for digital images
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机译：基于特征的检测和上下文区分分类的数字图像
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摘要
Detection and classification of targets in a digital image is accomplished by evaluating windowed portions of the image. A feature set is generated for each of a plurality of overlapping windowed portions, a weighted sum is formed for each portion based upon its feature set, and a context matrix is defined for each window. A score is formed from each context matrix and is normalized for each window. A threshold criteria is compared to a maximum score for each window. Each window having its maximum score satisfy the threshold criteria is classified as a possible target window and is assigned to a group based on location of the possible target window and its maximum score. A group score is formed for each group and compared to a group threshold criteria. Each group having its corresponding group score satisfying the group threshold criteria is classified as a target.
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