Characteristic analysis of Otsu threshold and its applications

作     者：Xu, Xiangyang Xu, Shengzhou Jin, Lianghai Song, Enmin 

作者机构：Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China Educ Minist Image Proc & Intelligent Control Key Lab Wuhan 430074 Hubei Peoples R China 

出 版 物：《PATTERN RECOGNITION LETTERS》 (模式识别快报)

年 卷 期：2011年第32卷第7期

页      面：956-961页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Science Foundation of China International Science and Technology Cooperation Project [2009DFA12290] 

主　　题：Image segmentation Threshold selection Otsu criterion 

摘      要：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.