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Proceedings Paper

Fast two-dimensional entropic thresholding algorithm
Author(s): Wen-Tsuen Chen; Chia-Hsien Wen; Chin-Wen Yang
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Paper Abstract

Two-dimensional entropic thresholding is one of the important thresholding techniques for image segmentation. Usually, the global threshold vector is selected from L2 (gray level, local average) pairs through a `maximum' optimization procedure with O(L4) computation complexity. This paper proposes a fast two-phase 2D entropic thresholding algorithm. In order to reduce the computation time, we estimate 9L2/3 candidate threshold vectors from a quantized image of the original in advance. The global threshold vector is then obtained by checking candidates only. The optimal computation complexity is O(L8/3) by quantizing the gray level in L2/3 levels. Experimental results show that the processing time of each image is reduced from more than two hours to about two minutes. The required memory space is also greatly reduced.

Paper Details

Date Published: 22 October 1993
PDF: 12 pages
Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); doi: 10.1117/12.157873
Show Author Affiliations
Wen-Tsuen Chen, National Tsing Hua Univ. (Taiwan)
Chia-Hsien Wen, National Tsing Hua Univ. (Taiwan)
Chin-Wen Yang, Taichung Veterans General Hospital (Taiwan)


Published in SPIE Proceedings Vol. 2094:
Visual Communications and Image Processing '93
Barry G. Haskell; Hsueh-Ming Hang, Editor(s)

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