A Self-adaptive Segmentation Method by Fusion of Multi-color Space Components

摘要

This paper presents a new, simple, and efficient segmentation approach. Firstly, choose the best segmentation components among six different color spaces. Then, Histogram and SFCM techniques are applied for initialization of segmentation. Finally, fuse the segmentation results and merge similar regions. Extensive experiments have been taken on Berkeley image database by using the proposed algorithm. The results show that, compared with some classical segmentation algorithms, our method could achieve better image partitioning and better performance.