Integrating Region Distribution and Edge Detection for Color Image Segmentation

Abstract

In this paper, we propose a new approach which integrates the region distribution and edge detection to achieve ideal results of color image segmentation. Firstly, we develop a histogram classification algorithm to classify color vectors and create binary trees for color image quantization, and we generate seeds for region growing from histogram classification automatically and obtain the initial regions. And further, the fast entropic thresholding algorithm and our multi-entropic-thresholding algorithm provide mechanisms for global and local edges detection respectively. Then, we integrate the information of regions and edges for eliminating texture regions, as well as small regions are merged by the size ratio of regions to overall regions with the same color vectors. Finally, the experimental results will show the results of color image segmentation.