This paper describes a new method for fuzzy segmentation based on spatial constraints. Taking into account the neighborhood influence two techniques are used. First a new feature is derived from Peano scans to represent a spatial relationship among neighbors. Second we incorporate a regularization term to fuzzy C-means algorithm (FCM). The algorithm is tested on both synthetic and multispectral images. Experimental results are presented and discussed. They show the effectiveness of the method.
A modified FCM with optimal Peano scans for image segmentation
IEEE International Conference on Image Processing 2005 ; 3 ; III-840
2005-01-01
139765 byte
Conference paper
Electronic Resource
English
A Modified Fcm with Optimal Peano Scans for Image Segmentation
British Library Conference Proceedings | 2005
|Optimal nonlinear interpolation of image line scans [5014-58]
British Library Conference Proceedings | 2003
|Concurrent edge/region detection from a Peano scan
IEEE | 2001
|Concurrent Edge/Region Detection from a Peano Scan
British Library Conference Proceedings | 2001
|Posture Recognition and Segmentation from 3D Human Body Scans
British Library Conference Proceedings | 2002
|