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Journal of Biomedical Optics

Automatic threshold selection using histogram quantization
Author(s): Yue Wang; Tulay Adali; Shih-Chung Benedict Lo
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Paper Abstract

An automatic threshold selection method is proposed for biomedical image analysis based on a histogram coding scheme. The threshold values can be determined based on the well-known Lloyd–Max scalar quantization rule, which is optimal in the sense of achieving minimum mean-square-error distortion. An iterative self-organizing learning rule is derived to determine the threshold levels. The rule does not require any prior information about the histogram, hence is fully automatic. Experimental results show that this new approach is easy to implement yet is highly efficient, robust with respect to noise, and yields reliable estimates of the threshold levels.

Paper Details

Date Published: 1 April 1997
PDF: 7 pages
J. Biomed. Opt. 2(2) doi: 10.1117/12.268965
Published in: Journal of Biomedical Optics Volume 2, Issue 2
Show Author Affiliations
Yue Wang, Georgetown Univ. (United States)
Tulay Adali, Univ. of Maryland/Baltimore County (United States)
Shih-Chung Benedict Lo, Georgetown Univ. Medical Ctr. (United States)


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