关键词: 图像分割, 阈值, 最大熵, 梯度, 细节信息

Abstract: Combining the two essential characteristics of the image, the gradient and the gray level, a threshold segmentation approach using maximum entropy with the gradient boundary control was proposed. In this approach, a boundary gradient controlling function was defined to quantify the richness of the detail information in the images. The local maximums of this function indicated a possible threshold set for the image segmentation. Within this set, a best threshold could be selected by using maximum entropy principle to get the binary image. The experimental results show that the regions segmented by this method can contain more semantics of the images for the ample detail information reserved in it. Moreover, this method is also with noise immunity in some degrees.

Key words: image segmentation, threshold, maximum entropy, gradient, detail information