Trace Inference, Curvature Consistency, and Curve Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge-Labeling Using Dictionary-Based Relaxation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Edge Detectors for Ramp Edges
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Smoothing: A General Tool for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reasoning About Edges in Scale Space
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reinforcement of Linear Structure using Parametrized Relaxation Labeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
Adaptive Determination of Filter Scales for Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new fuzzy relaxation algorithm for image enhancement
International Journal of Knowledge-based and Intelligent Engineering Systems
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
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We present a method for detecting and labeling the edge structures in digital gray-scale images in two distinct stages: First, a variant of the cubic facet model is applied to detect the location, orientation and curvature of the putative edge points. Next, a relaxation labeling network is used to reinforce meaningful edge structures and suppress noisy edges. Each node label of this network is a 3D vector parameterizing the orientation and curvature information of the corresponding edge point. A hysterisis step in the relaxation process maximizes connected contours. For certain types of images, prefiltering by adaptive smoothing improves robustness against noise and spatial blurring.