Index-Guided Natural Image Segmentation

摘要：

Natural image segmentation has been a major research topic in recent years. From the viewpoint of clustering, image segmentation could be solved by Self-Organizing Map (SOM) based methods. In this paper we combine a saliency map with SOM and A-means method (SOM-KS) to segment a natural image. Features of saliency map, intensity and L*u*v* color space are trained with SOM and followed by a A-means method to cluster the prototype vectors. The guidance of an entropy or quantitative evaluation index helps to make a more precise segmentation. Comparison shows that the proposed unsupervised method can achieve better segmentation results, less computational load and no human intervention with the guidance of the entropy index.

关键词： Color Image Segmentation Self-Organizing Map Saliency Map k-means Entropy Index Quantitative Index

作者: Dongxiang Chi Ming Li Ying Zhao Jing Hu

作者单位: School of Electronics & Information Shanghai Dianji University Shanghai, China

会议类型: 国际会议

会议名称: 2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)

会议地点: 上海

会议语种:英文

页码: 1273-1276

在线出版日期: 2011-10-15（万方平台首次上网日期，不代表论文的发表时间）