Characteristic analysis of Otsu threshold and its applications
Characteristic analysis of Otsu threshold and its applications
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Otsu阈值特性分析及其应用
DOI：
10.1016/j.patrec.2011.01.021
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发表时间：
2011-05-01
影响因子：
5.1
通讯作者：
Song, Enmin
中科院分区：
文献类型：
--
作者：
Xu, Xiangyang;Xu, Shengzhou;Song, Enmin
本文证明了大津阈值等于按此阈值划分的两类平均水平的平均值。因此，当两个类的类内方差不同时，阈值偏向方差较大的类。结果，属于这个类的部分像素将被误分类到具有较小方差的另一类中。针对这一问题，在分析大津阈值的基础上，提出了一种限制灰度搜索范围的改进大津算法。实验结果表明，新算法与大津方法相比具有明显的优越性。(C)2011 Elsevier B.V.保留所有权利。
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.