Optimal ramp edge detection using expansion matching
Zhiqian Wang
Raghunath Rao, K.
Ben-Arie, J.
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: Nov 1996
Volume: 18,
Issue: 11
On page(s): 1092-1097
ISSN: 0162-8828
References Cited: 16
CODEN: ITPIDJ
INSPEC Accession Number: 5446359
Digital Object Identifier: 10.1109/34.544078
Current Version Published: 2002-08-06
Abstract
In practical images, ideal step edges are actually transformed
into ramp edges, due to the general low pass filtering nature of imaging
systems. This paper discusses the application of the expansion matching
(EXM) method for optimal ramp edge detection. EXM optimizes a novel
matching criterion called discriminative signal-to-noise ratio (DSNR)
and has been shown to robustly recognize templates under conditions of
noise, severe occlusion, and superposition. We show that our ramp edge
detector performs better than the ramp detector obtained from Canny's
criteria in terms of DSNR and is relatively easier to derive for various
noise levels and slopes
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