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Texture Analysis and Cartographic Feature Extraction.
ARMY ENGINEER TOPOGRAPHIC LABS FORT BELVOIR VA
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Investigations into using various image descriptors as well as developing interactive feature extraction software on the Digital Image Analysis LaboratoryDIAL have culminated in a revised procedure to test statistical classification methods. An interactive experiment using this procedure was performed and showed that of the image descriptors tested, the most significant was a two component vector derived from an average and a standard deviation measure of gray shades. The texture measures failed to deliver any increase in performance for the classifier. In general, this report shows that statistical classification methods are insufficient by themselves to deliver the performance needed in a semi-automated cartographic feature extraction system. Originator-supplied keywords Ad-Hoc image descriptor Bayes classifier Bhattachryya distance Clustering Digital Image Analysis Laboratory DIAL Feature extraction Interactive processing Laws texture measure Principal components Raster processing Relaxation.
APPROVED FOR PUBLIC RELEASE