南京理工大学学报（自然科学版）2012，Vol.36Issue(2)：232-237,6.
一种非监督道路场景分割方法
Unsupervised Road Scene Segmentation Method
摘要
Abstract
To solve the problems that lots of training samples are needed in (he road scene segmentation and the changes of different roads cause the segmentation error easily, this paper proposes an unsupervised road scene segmentation method. First, X-means clustering method is applied to the first image for its initial segmentation; Second, graph cut optimization algorithm is used to minimize the total image energy to get the optimal segmentation. With the computed class centers of the segmented image, the next image is also optimized by graph cut. Experimental results show that this method can segment the road scene quickly without quantities of training samples,and can keep efficient in changing of different road types关键词
道路场景分割/XYZ颜色空间/Gabor纹理特征/K均值聚类/图割Key words
road scene segmentation / XYZ color space /Gabor texture /K-means clustering/ graph cut分类
信息技术与安全科学引用本文复制引用
张浩峰,业巧林,赵春霞,杨静宇..一种非监督道路场景分割方法[J].南京理工大学学报（自然科学版）,2012,36(2):232-237,6.基金项目
高等学校博士点专项基金(20093219120025) （20093219120025）
国家自然科学基金(61101197) （61101197）
