一种形态学彩色图像多尺度分割算法  

A Morphological Algorithm for Color Image Multi-scale Segmentation

作　　者：彭启民[1] 贾云得[1] 

机构地区：[1]北京理工大学信息科学技术学院计算机科学与工程系,北京100081

出　　处：《中国图象图形学报》2006年第5期635-639,I0001,共6页Journal of Image and Graphics

基　　金：国家自然科学基金项目(60476039)

摘　　要：为了对彩色图像进行快速有效的分割,提出了一种用于分割彩色图像的多尺度形态学算法。该算法首先用基于张量梯度的彩色分水岭算法来得到初始分割结果,即局部水平集连通区域,并综合考虑了面积和色彩计算区域间的相似性,构造了区域间的RAG(region ad jacency graph)和NNG(nearest ne ighbor nraph),用于后续形态学处理;接着,基于HSV空间中的色彩全序关系,定义了彩色形态算子;然后采用顶点塌缩算法实现的彩色形态学开闭算子生成了所需的非线性尺度空间;最后,利用图像中的极值点与物体间的对应关系,逐级提取图像中包含的物体来得到分层级的表示,并用区域在不同尺度下熵的变化来决定尺度树的构成,从而完成了彩色图像的分割。试验结果表明,该算法不仅具有出色的形状保持能力,而且可提高计算效率。A multi-scale morphological algorithm for color images segmentation is proposed in this paper. At first, color watershed transform is applied based on tensor gradient to get initial segmentation, i.e. local level connected sets. Both area and color are considered to calculate the similarity between adjacent regions. Then, a RAG（ Region Adjacency Graph） and a NNG（ Nearest Neighbor Graph） are constructed to accelerate following morphological processing. Finally, color morphological operators are defined based on a special full order relation of color vectors in HSV model. Morphological opening-closing is implemented using vertex-collapse algorithm. A nonlinear scale space will be constructed efficiently with perfect shape preserving. Since extrema in an image are always associated with objects, particular objects are extracted at different scales. Entropy criterion is adopted to control the content contained in the final scale tree.

关 键 词：图像分割 彩色 形态学 非线性尺度空间 顶点塌缩 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]