A Multilevel Thresholding Method Based on Cross Entropy and Genetic Algorithms

Abstract

Threshold selection is one of the most important issues in image processing. In this paper, a general technique for multilevel thresholding based on cross entropy is proposed. Then, a genetic algorithm is designed especially for searching for the near-optimal or optimal thresholds. The effectiveness and efficiency of the proposed method is demonstrated by using well-known images.