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An Edge Detection Technique Using the Facet Model and Parameterized Relaxation Labeling
April 1997 (vol. 19 no. 4)
pp. 328-341

Abstract—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.

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Index Terms:
Edge detection, relaxation labeling, facet model, curve enhancement, computer vision, image analysis.
Citation:
Ioannis Matalas, Ralph Benjamin, Richard Kitney, "An Edge Detection Technique Using the Facet Model and Parameterized Relaxation Labeling," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 4, pp. 328-341, April 1997, doi:10.1109/34.588006
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