中文摘要：

针对传统图像分割方法在处理梯度变化较大的图像中存在的缺陷,以随机游走算法为基础,在原始的像素的灰度信息的基础上,融合了像素间的梯度差信息作为图网络的权重,以更好地描述像素与其相邻像素间的关系,通过用户指定的种子点信息,借助于电路模拟以及线性方程的系统,使得随机游走者从每个非种子点沿着最大概率的边逐渐走向正确的标记点（目标点或背景点）即为其最可能属于的区域,从而最终实现图像的分割.实验结果表明,方法适合于梯度变化较大的图像,不仅保留了原有算法抗噪声的优势,而且运算效率较高,是一种有效的图像分割方法.

英文摘要：

Owing to traditional methods of image segmentation exist defects in dealing with images of larger gradient changes,this paper integrate inter-pixel gradient differentia information on the basis of original pixel gray information in the random walks to assign weights to edges of figure to better describe relationship of adjacent pixel,by means of the information of seed points designated by user,with the aid of circuit simulation and systemof linear equation to guide the random walkers gradually move from of each of the unseeded points along the edges with maximum probabilities to the right marker point（object or background） ,which is belonged to the most probable region to carry out the segmentation of image.The experimental results show that this method is fit for processing images with larger gradient changes,which not only retain the anti-noise advantage of original algorithm,but also have higher computing efficiency.To sum up,it’s an effective method of image segmentation.