Automatic Feature Extraction/Algorithm Testing.
Final evaluation rept. 28 Sep 84-30 Sep 85,
AUTOMETRIC INC ROME NY
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Feature extraction results using an Improved Texture Clustering Algorithm were compared to photo interpreters manual segmentationclassification results. The clustering algorithm segments digital images via texture and edge attributes. The probability of detecting a target or feature is increased if the number of segments is reduced therefore, the algorithm merges segments via edge thresholds. Evaluation showed general agreement, but the edge attributes would apply more to target detection than to feature classification. Keywords Digital image processing. Author