A fast numerical method for finding the optimal threshold for image segmentation

In this paper, we propose a fast numerical algorithm for finding the optimal threshold for segmenting gray scale images. In the proposed method, several fuzzy entropy measures are introduced and the objective is to locate the gray level that possesses the minimum entropy. Instead of having to calculate the entropy for every gray level and determining the gray level where the entropy is minimum, the fixed point iteration (FPI) method is used to significantly speed up the process. In doing so, the optimal threshold may be quickly obtained within a few number of evaluations. To show the validity of our proposed algorithm, we test 7 types of fuzzy entropy measures on several images. The experimental results show that the proposed algorithm is much faster without loss of performance than the methods in earlier surveys.