Image segmentation using spectral clustering

This paper focuses on how to automatically determine the suitable clustering number in image segmentation and designs an algorithm of CANA using spectral clustering. Experiment results indicate that ACNA can provide superior performance. An application sample in image punching is introduced

[1]  Kun Huang,et al.  A unifying theorem for spectral embedding and clustering , 2003, AISTATS.

[2]  Martine D. F. Schlag,et al.  Spectral K-way ratio-cut partitioning and clustering , 1994, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..

[3]  Martine D. F. Schlag,et al.  Spectral K-Way Ratio-Cut Partitioning and Clustering , 1993, 30th ACM/IEEE Design Automation Conference.

[4]  Michael I. Jordan,et al.  On Spectral Clustering: Analysis and an algorithm , 2001, NIPS.

[5]  Jitendra Malik,et al.  Efficient spatiotemporal grouping using the Nystrom method , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.