RPCCL Clustering and its Evaluation in Image Segmentation

摘要：

In this paper, we propose a new image segmentation approach based on rival penalized controlled competitive learning (RPCCL) and color quantization technique. First, we perform median filtering on input image. Second, the initial color centers are selected by color quantization algorithm. Then after several iterations, the RPCCL clustering converges and produces the final segmentation results. We carry out experiments and quantitative evaluation based on Berkeley Segmentation Database (BSD300). The results show that RPCCL method is superior to K-means clustering.

关键词： Clustering Segmentation RPCCL K-means clustering Segmentation evaluation

作者: Xinhui LI Runping SHEN Renxi CHEN

作者单位: School of Remote Sensing Nanjing University of Information & Science Technology Nanjing, China School of Geoscience and Engineering Hohai University Nanjing, China

会议类型: 国际会议

会议名称: 2012 International Conference on Computer Science and Electronic Engineering(2012 IEEE计算机科学与电子工程国际会议 ICCSEE 2012)

会议地点: 杭州

会议语种:英文

页码: 517-521

在线出版日期: 2012-03-23（万方平台首次上网日期，不代表论文的发表时间）