关键词: 遗传算法, 灰度-梯度熵, 多阈值, 图像分割, 积分图

Abstract: Due to considering the gray level spatial distribution information, some image segmentation technologies based on entropy threshold can enhance the thresholding segmentation performance. However, they still cannot distinguish image edges and noise well. Even though GLGM (gray-level & gradient-magnitude) entropy can effectively solve the problem, it cannot segment effectively multi-objective and complex image. So, this paper proposes image segmentation with multi-threshold of GLGM entropy based on genetic algorithm. In the proposed method, integral figure is introduced in order to make threshold searching dimension from original O(9×L) to O(L), and the single threshold segmentation of GLGM entropy is further extended to multi-threshold segmentation. Lastly, the real-code-GA is used to search the best thresholds. The simulation results show that this method can be effectively applied for the multi-threshold segmentation of complex images.

Key words: genetic algorithm, gray-level &, gradient-magnitude entropy, multi-threshold, image segmentation, integral figure