DocumentCode :
1025316
Title :
A Context Classifier
Author :
Haralick, Robert M. ; Joo, Hyonam
Author_Institution :
Department of Electrical Engineering, University of Washington, Seattle, WA 98195
Issue :
6
fYear :
1986
Firstpage :
997
Lastpage :
1007
Abstract :
All other things being equal, context classifiers have a higher identification accuracy than pixel independent classifiers. This paper discusses a classifier whose context for each pixel is the best row monotonically increasing path including the given pixel. Use of such a context results in a two pass algorithm in which both the top down and bottom up pass require only two rows of data and whose computational complexity per pixel is constant independent of the size of image or the length of the best context path including the given pixel.
Keywords :
Computational complexity; Decision making; Frequency; Labeling; Layout; Machine vision; Pattern recognition; Pixel; Stochastic processes; Text recognition;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.1986.289563
Filename :
4072572
Link To Document :
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