A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Relaxation labelling algorithms-a review
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On compatibility and support functions in probabilistic relaxation
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Edge detection and motion detection
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Contextual decision rule for region analysis
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Finding Edges and Lines in Images
Finding Edges and Lines in Images
Constrained Regularized Differentiation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Probabilistic Relaxation Scheme and Its Application to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Edge Detection Technique Using the Facet Model and Parameterized Relaxation Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Dynamics of Nonlinear Relaxation Labeling Processes
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
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Neural Edge Enhancer for Supervised Edge Enhancement from Noisy Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Probabilistic relaxation labeling by Fokker-Planck diffusion on a graph
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
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An improved application of probabilistic relaxation to edge labeling is presented. The improvement derives from the use of a representation of the edge process that is internally consistent and which utilizes a more complex description of edge structure. The application uses a dictionary to represent permitted labelings of the entire context-conveying neighborhood of each pixel. Details are given of the dictionary approach and the related representation of the edge process. A comparison with other edge-postprocessing strategies is provided.