关键词: 条件熵阈值法, 灰度-梯度共生矩阵, 加权, 图像分割

Abstract: The maximum entropic threshold method is a common image segmentation technology based on the “gray-gray means”.This approach focuses on extracting the internal information，but ignores the edge information.Using the image gradient information，this paper establishes “gray-gradient co-occurrence matrix”，combined with the maximum conditional entropy threshold selection formula.A 2-D weighted maximum entropic threshold method is presented to obtain the internal and edge informations of the image.The results show that this method can preserve the more image edge information.The conditional entropy can be weighted，the weights can be adjusted according to the actual requirements，the segmentation results both with internal and edge informations of the image can be obtained.

Key words: conditional entropic threshold method, gray-gradient co-occurrence matrix, weighted, image segmentation