Multi-Scale Contour Segmentation

Effective local segmentation of contours is an important problem which arises in occluded object recognition as well as other areas. For any recognition system to perform successfully, the segmentation procedure used must be robust in presence of noise and local distortions of shape. Furthermore, it should be based on geometric invariants so that the segmentation will not be affected by arbitrary choices.

[1]  Farzin Mokhtarian,et al.  A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Paul L. Rosin.  Representing curves at their natural scales , 1992, Pattern Recognit..

[3]  Farzin Mokhtarian.  Silhouette-Based Object Recognition with Occlusion through Curvature Scale-Space , 1996, ECCV.

[4]  Gérard G. Medioni,et al.  Structural Indexing: Efficient 3-D Object Recognition , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Farzin Mokhtarian.  Fingerprint theorems for curvature and torsion zero-crossings , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Olivier D. Faugeras,et al.  HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Roland T. Chin,et al.  Scale-Based Detection of Corners of Planar Curves , 1992, IEEE Trans. Pattern Anal. Mach. Intell..