摘要
提出一种基于分量直方图的自适应分割方法 .首先对图像的 3个分量统计直方图进行自适应分割 ,确定出各分量的分类数目及类的取值范围 ;然后 ,对分割类进行分量间组合 ,获得原图像中主要的几种颜色 ;最后以这些颜色作为聚类中心 ,按照颜色相似性准则对图像进行聚类分割 .在移动机器人CASIA 1上进行的实验证明 :该算法实现了图像主要区域的自适应分割与提取 。
This paper presents a fast adaptive segmentation method for mobile robot based on histograms of component. After adaptive segmentation of components histograms of visual image, principal colors and their areas are determined. Then through combining the color areas of these component value, image can be divided into several different colors. Finally, according to principle of color similarity, the image is segmented by cluster segmentation method, with these different colors as the clustering center. Experiments on CASIA 1 mobile robot proves that this method can adaptively segment and detect principal areas of the original image, and can meet real time needs of mobile robot for visual signal processing.
出处
《机器人》
EI
CSCD
北大核心
2004年第6期524-528,共5页
Robot
关键词
自适应分割
移动机器人
彩色图像
分量直方图
adaptive segmentation
mobile robot
color image
histogram of component
