A Fast Algorithm for Multilevel Thresholding

廖炳松(Ping-Sung Liao) ； 陳澤生(Tse-Sheng Chen) ； 詹寶珠(Pau-Choo Chung)

《Journal of Information Science and Engineering》 17卷5期 (2001/09) Pp. 713-727

https://doi.org/10.6688/JISE.2001.17.5.1

並列摘要

Otsu reference proposed a criterion for maximizing the between-class variance of pixel intensity to perform picture thresholding. However, Otsu's method for image segmentation is very time-consuming because of the inefficient formulation of the between-class variance. In this paper, a faster version of Otsu's method is proposed for improving the efficiency of computation for the optimal thresholds of an image. First, a criterion for maximizing a modified between-class variance that is equivalent to the criterion of maximizing the usual between-class variance is proposed for image segmentation. Next, in accordance with the new criterion, a recursive algorithm is designed to efficiently find the optimal threshold. This procedure yields the same set of thresholds as the original method. In addition, the modified between-class variance can be pre-computed and stored in a look-up table. Our analysis of the new criterion clearly shows that it takes less computation to compute both the cumulative probability (zeroth order moment) and the mean (first order moment) of a class, and that determining the modified between-class variance by accessing a look-up table is quicker than that by performing mathematical arithmetic operations. For example, the experimental results of a five-level threshold selection show that our proposed method can reduce down the processing time from more than one hour by the conventional Otsu's method to less than 107 seconds.

並列關鍵字

Otsu's thresholding ； image segmentation ； picture thresholding ； multilevel thresholding ； recursive algorithm