@article{(Open Science Index):https://publications.waset.org/pdf/12161, title = {Color Image Segmentation Using Competitive and Cooperative Learning Approach}, author = {Yinggan Tang and Xinping Guan}, country = {}, institution = {}, abstract = {Color image segmentation can be considered as a cluster procedure in feature space. k-means and its adaptive version, i.e. competitive learning approach are powerful tools for data clustering. But k-means and competitive learning suffer from several drawbacks such as dead-unit problem and need to pre-specify number of cluster. In this paper, we will explore to use competitive and cooperative learning approach to perform color image segmentation. In competitive and cooperative learning approach, seed points not only compete each other, but also the winner will dynamically select several nearest competitors to form a cooperative team to adapt to the input together, finally it can automatically select the correct number of cluster and avoid the dead-units problem. Experimental results show that CCL can obtain better segmentation result.}, journal = {International Journal of Computer and Information Engineering}, volume = {2}, number = {1}, year = {2008}, pages = {227 - 230}, ee = {https://publications.waset.org/pdf/12161}, url = {https://publications.waset.org/vol/13}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 13, 2008}, }