Automatic Threshold Selection Based On Information Gain

R. Subramanian; Rajiv Mehrotra

doi:10.1117/12.947682

12 October 1988 Automatic Threshold Selection Based On Information Gain

R. Subramanian, Rajiv Mehrotra

Proceedings Volume 0956, Piece Recognition and Image Processing; (1988) https://doi.org/10.1117/12.947682
Event: SPIE International Symposium on Optical Engineering and Industrial Sensing for Advance Manufacturing Technologies, 1988, Dearborn, MI, United States

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.

Citation Download Citation

R. Subramanian and Rajiv Mehrotra "Automatic Threshold Selection Based On Information Gain", Proc. SPIE 0956, Piece Recognition and Image Processing, (12 October 1988); https://doi.org/10.1117/12.947682

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