Edge detection, classification, and measurement

Author

Lee, David

Author_Institution

AT&T Bell Lab., Murray Hill, NJ, USA

fYear

1989

fDate

4-8 Jun 1989

Firstpage

2

Lastpage

10

Abstract

An edge detector is proposed which consists of a pair of a pattern and a linear filter. It is shown that for an edge in the input signal, there is a scaled pattern in the filter response. The location of the pattern is the location of the edge, and the scaling factor of the pattern is the size of the edge. Therefore the problem of edge detection and measurement is reduced to searching for the (scaled) pattern in the filter response. In the presence of noise, the pattern matching is approximate. A statistical approach for the pattern search is proposed. Optimal detectors which minimize the effects of noise are studied; for white noise, the optimal detectors are natural splines. Testing results on real images are reported

Keywords

filtering and prediction theory; pattern recognition; picture processing; statistical analysis; edge detection; linear filter; pattern matching; pattern recognition; picture processing; scaled pattern; scaling factor; splines; statistical approach; white noise; Detectors; Image edge detection; Layout; Lighting; Nonlinear filters; Optical filters; Optical noise; Reflectivity; Testing; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1989. Proceedings CVPR '89., IEEE Computer Society Conference on

Conference_Location

San Diego, CA

ISSN

1063-6919

Print_ISBN

0-8186-1952-x

Type

conf

DOI

10.1109/CVPR.1989.37822

Filename

37822