An edge detection technique using the facet model and parameterized relaxation labeling

Author

Matalas, Loannis ; Benjamin, Ralph ; Kitney, Richard

Author_Institution

Dept. of Electr. & Electron. Eng., Imperial Coll. of Sci., Technol. & Med., London, UK

Volume

19

Issue

4

fYear

1997

fDate

4/1/1997 12:00:00 AM

Firstpage

328

Lastpage

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 hysteresis step in the relaxation process maximizes connected contours. For certain types of images, prefiltering by adaptive smoothing improves robustness against noise and spatial blurring

Keywords

edge detection; noise; relaxation theory; smoothing methods; 3D vector; adaptive smoothing; connected contour maximization; cubic facet model; digital gray-scale images; edge detection; edge suppression; facet model; meaningful edge structure reinforcement; node label; noise robustness; parameterized relaxation labeling; prefiltering; putative edge point curvature; putative edge point location; putative edge point orientation; relaxation labeling network; relaxation process; spatial blurring robustness; Degradation; Face detection; Filters; Gaussian noise; Gray-scale; Image edge detection; Labeling; Smoothing methods; Surface contamination; Surface fitting;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.588006

Filename

588006