期刊
PATTERN RECOGNITION LETTERS
卷 32, 期 7, 页码 956-961出版社
ELSEVIER
DOI: 10.1016/j.patrec.2011.01.021
关键词
Image segmentation; Threshold selection; Otsu criterion
资金
- National Science Foundation of China [60972098]
- International Science and Technology Cooperation Project [2009DFA12290]
This paper proves that Otsu threshold is equal to the average of the mean levels of two classes partitioned by this threshold. Therefore, when the within-class variances of two classes are different, the threshold biases toward the class with larger variance. As a result, partial pixels belonging to this class will be mis-classified into the other class with smaller variance. To address this problem and based on the analysis of Otsu threshold, this paper proposes an improved Otsu algorithm that constrains the search range of gray levels. Experimental results demonstrate the superiority of new algorithm compared with Otsu method. (C) 2011 Elsevier B.V. All rights reserved.
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