大津法
像素
差异(会计)
模式识别(心理学)
航程(航空)
人工智能
班级(哲学)
计算机科学
数学
图像(数学)
算法
统计
图像分割
业务
会计
复合材料
材料科学
作者
Xiangyang Xu,Shengzhou Xu,Lianghai Jin,Enmin Song
标识
DOI:10.1016/j.patrec.2011.01.021
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 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.
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