Edge detection and curve enhancement using the facet model and parametrized relaxation labelling

We present a method for detecting and labeling the edge structures in digital grey-scale images in two distinct stages: 1) a variant of the cubic facet model detects location, orientation and curvature of the putative edge points; and 2) a relaxation labeling network reinforces meaningful edge structures and suppresses noisy edges. Each node label of this network is a 3D vector parametrizing the orientation and curvature of the corresponding edge point. A hysteresis step in the relaxation process maximizes connected contours. For certain images, prefiltering by adaptive smoothing improves robustness against noise and spatial blurring.