Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
International Journal of Computer Vision
Clustering Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Active Contour Model without Edges
SCALE-SPACE '99 Proceedings of the Second International Conference on Scale-Space Theories in Computer Vision
Digital Image Processing Using MATLAB
Digital Image Processing Using MATLAB
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
A cost-function approach to rival penalized competitive learning (RPCL)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Texture classification and segmentation using wavelet frames
IEEE Transactions on Image Processing
Rival penalized competitive learning for clustering analysis, RBF net, and curve detection
IEEE Transactions on Neural Networks
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In this paper, we propose a competitive learning based Chan-Vese model (CLCV) for two-phase image segmentation by coupling the Chan-Vese model and the rival penalized competitive learning mechanism from the point of view of the cost function for the DSRPCL algorithm. Specifically, the CLCV model based approach to image segmentation incorporates the mechanism of rival penalized competitive learning into the evolution of the level set function so that there emerge certain repulsive forces between the foreground and background classes, which lead to more accurate segmentations of the image. Experimental results on several real-world images have validated the advantages of the proposed CLCV model over the original Chan-Vese model on integral segmentation, smooth boundaries and robustness to noises.