Characteristic analysis of Otsu threshold and its applications

Authors:
Xiangyang Xu;Shengzhou Xu;Lianghai Jin;Enmin Song
Affiliations:
School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China and Key Laboratory of Education Ministry for Image Processing and Intelligent C ...;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China and Key Laboratory of Education Ministry for Image Processing and Intelligent C ...;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China and Key Laboratory of Education Ministry for Image Processing and Intelligent C ...;School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China and Key Laboratory of Education Ministry for Image Processing and Intelligent C ...
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

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 misclassified 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.