DocumentCode :
1127059
Title :
Optimal edge detectors for ramp edges
Author :
Petrou, Maria ; Kittler, Josef
Author_Institution :
Dept. of Electron. & Electr. Eng., Surrey Univ., Guildford, UK
Volume :
13
Issue :
5
fYear :
1991
fDate :
5/1/1991 12:00:00 AM
Firstpage :
483
Lastpage :
491
Abstract :
It is argued that the best way to model an edge is by assuming all ideal mathematical function passed through a low-pass filter and and immersed in noise. Using techniques similar to those developed by J. Canny (1983, 1986) and L.A. Spacek (1986), optimal filters are derived for ramp edges of various slopes. The optimal nonrecursive filter for ideal step edges is then derived as a limiting case of the filters for ramp edges. Because there are no step edges in images, edge detection is improved when the ramp filter is used instead of the filters developed for step edges. For practical purposes, some convolution masks are given which can be used directly for edge detection without the need to go into the details of the subject
Keywords :
filtering and prediction theory; pattern recognition; picture processing; convolution masks; edge detectors; optimal filters; ramp edges; Boundary conditions; Convolution; Detectors; Differential equations; Image edge detection; Image processing; Limiting; Low pass filters; Mathematical model; Signal to noise ratio;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/34.134047
Filename :
134047
Link To Document :
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