DocumentCode :
3069136
Title :
Edge detection and curve enhancement using the facet model and parametrized relaxation labelling
Author :
Matalas, I. ; Benjamin, R. ; Kitney, R.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci. Technol. & Med., London, UK
Volume :
1
fYear :
1994
fDate :
9-13 Oct 1994
Firstpage :
1
Abstract :
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
Keywords :
edge detection; adaptive smoothing; cubic facet model; curve enhancement; digital grey-scale images; edge detection; edge structures; iterative updating; noisy edge suppression; relaxation labelling; Biomedical imaging; Educational institutions; Face detection; Filters; Image edge detection; Labeling; Noise level; Noise robustness; Smoothing methods; Surface fitting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1994. Vol. 1 - Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on
Conference_Location :
Jerusalem
Print_ISBN :
0-8186-6265-4
Type :
conf
DOI :
10.1109/ICPR.1994.576214
Filename :
576214
Link To Document :
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