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Proceedings Paper

Automatic Threshold Selection Based On Information Gain
Author(s): R. Subramanian; Rajiv Mehrotra
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Paper Abstract

An approach to automatic threshold selection based on information gain, is proposed. The probability distribution of gray levels can be utilized to compute the information content of the image using entropic measures. An objective function representing the information gain provided by the threshold gray level with respect to the other gray levels is defined. The gray level value that maximizes the discriminant function is selected as the threshold value for the input gray level image to provide an output binary image.

Paper Details

Date Published: 12 October 1988
PDF: 4 pages
Proc. SPIE 0956, Piece Recognition and Image Processing, (12 October 1988); doi: 10.1117/12.947682
Show Author Affiliations
R. Subramanian, University of South Florida (United States)
Rajiv Mehrotra, University of South Florida (United States)


Published in SPIE Proceedings Vol. 0956:
Piece Recognition and Image Processing
Wayne Wiitanen, Editor(s)

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