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Costianes et al., 2010 - Google Patents

Gray-level co-occurrence matrices as features in edge enhanced images

Costianes et al., 2010

Document ID
16488415820255189554
Author
Costianes P
Plock J
Publication year
Publication venue
2010 IEEE 39th Applied Imagery Pattern Recognition Workshop (AIPR)

External Links

Snippet

In 1973, Haralick, Shanmugam, and Dinstein published a paper in the IEEE Transactions on Systems, Man, and Cybernetics which proposed using Gray-Level Co-occurrence Matrices (GLCM) as a basis to define 2-D texture. Over 14 different texture measures were defined …
Continue reading at ieeexplore.ieee.org (other versions)

Classifications

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    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/4671—Extracting features based on salient regional features, e.g. Scale Invariant Feature Transform [SIFT] keypoints
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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
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    • G06F17/30799—Information retrieval; Database structures therefor; File system structures therefor of video data using features automatically derived from the video content, e.g. descriptors, fingerprints, signatures, genre using low-level visual features of the video content

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