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Textural features for image classificationDescription of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.
Document ID
19740036331
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Haralick, R. M.
Dinstein, I.
(Kansas, University; Center for Research, Inc., Lawrence, Kan., United States)
Shanmugam, K.
(Wichita State University Wichita, Kan., United States)
Date Acquired
August 7, 2013
Publication Date
November 1, 1973
Subject Category
Instrumentation And Photography
Accession Number
74A19081
Funding Number(s)
CONTRACT_GRANT: DAAK02-70-C-0388
CONTRACT_GRANT: NAS5-21822
Distribution Limits
Public
Copyright
Other

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