摘要
为了提高传统的随机游走分割算法的性能,提出一种基于滑降算法的随机游走图像分割算法.利用图像的局部灰度信息进行滑降分割,将图像分割成多个小区域;把每个小区域作为一个节点,采用万有引力定律来定义各个节点之间的权值,利用随机游走算法产生最终的分割结果.实验结果表明,该算法有效地结合了滑降算法和随机游走算法的优点,提高了图像分割的速度和精度.
In order to improve the performance of traditional random walk algorithm, an image segmentation algorithm based on toboggan and random walk is proposed. The image is segmented into a large number of small patches using toboggan algorithm on the basis of local gray value, and each of such patches is considered as a node, then the law of gravity is used to define weights between the nodes. The final segmented image is produced with random walk algorithm. The results show that our proposed algorithm possesses the nice properties of the toboggan algorithm and random walk algorithm, is both efficient and accurate.
出处
《计算机辅助设计与图形学学报》
EI
CSCD
北大核心
2009年第8期1149-1154,共6页
Journal of Computer-Aided Design & Computer Graphics
基金
国家自然科学基金(60274099)
教育部博士点基金(20020145007)
关键词
加权图
滑降算法
万有引力算子
随机游走
weighted graph
toboggan algorithm
gravity algorithm
random walk