A Hybrid Method of Block-Based Region Growing and Visible Color Difference for Color Image Segmentation

Abstract

In this paper we propose a color image segmentation algorithm based on visible color difference and block-based region growing techniques. Firstly, the original image is divide into image blocks which are not overlapped; then, the mean and variance of each image black was calculated in CIEL*a*b* color space, and the image blocks were divided into homogeneous color blocks and texture blocks by the variance of it. The Initial seed regions are automatically selected depending on calculating the homogeneous color blocks’ color difference in CIEL*a*b* color space and spatial and adjacent information. The quadtree decomposition algorithm was applied to split and merge the texture blocks. Finally, the region growing and merging algorithm was to use and achieve the segmentation result. The experimental segmentation results hold favorable consistency in terms of human perception, and confirm effectiveness of the algorithm.