DocumentCode :
1134712
Title :
A Max-Min Measure for Image Texture Analysis
Author :
Mitchell, Owen R. ; Myers, Charles R. ; Boyne, William
Author_Institution :
School of Electrical Engineering, Purdue University
Issue :
4
fYear :
1977
fDate :
4/1/1977 12:00:00 AM
Firstpage :
408
Lastpage :
414
Abstract :
A new technique for image texture analysis is described which uses the relative frequency of local extremes in grey level as the principal measure. This method is invariant to multiplicative gain changes (such as caused by changes in illumination level or film processing) and is invariant to image resolution and sampling rate if the image is not undersampled. The algorithm described is computationally simple and can be implemented in hardware for real-time analysis. Comparisons are made between this new method and the spatial dependence method of texture analysis using 49 samples of each of eight textures. The new method seems just as accurate and considerably faster.
Keywords :
Digital image processing, feature extraction, pattern recognition, smoothing algorithms, texture analysis.; Algorithm design and analysis; Covariance matrix; Error analysis; Frequency; Image resolution; Image texture analysis; Lighting; Nearest neighbor searches; Pattern analysis; Pattern recognition; Digital image processing, feature extraction, pattern recognition, smoothing algorithms, texture analysis.;
fLanguage :
English
Journal_Title :
Computers, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9340
Type :
jour
DOI :
10.1109/TC.1977.1674850
Filename :
1674850
Link To Document :
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