彩色图像分割，鲁棒模式分析，低层次视觉，基于内容的索引

This is modified version of Dorin Comaniciu & Peter Meer work only to compile on modern Linux and with some bugfixes. Program is free only for educational or research purposes. Commercial use has to be permitted by the author http://www.caip.rutgers.edu/~comanici/segm_images.html Abstract: A general technique for the recovery of significant image features is presented. The technique is based on the mean shift algorithm, a simple nonparametric procedure for estimating density gradients. Drawbacks of the current methods (including robust clustering) are avoided. Feature space of any nature can be processed, and as an example, color image segmentation is discussed. The segmentation is completely autonomous, only its class is chosen by the user. Thus, the same program can produce a high quality edge image, or provide, by extracting all the significant colors, a preprocessor for content-based query systems. A 512x512 color image is analyzed in less than 10 sec