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Proceedings Paper

Localization performance measure and optimal edge detection
Author(s): Hemant D. Tagare; Rui J. P. de Figueiredo
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Paper Abstract

Recent developments in edge detection have exposed diiferent criteria to gauge the performance of edge detectors in the presense of noise. One of the criteria is "Localization", which is the ability of the edge detector to produce from noisy data a detected edge that is as close as possible to the true edge in the image. In this paper, we show the limitation of the localization criteria as previously formulated and propose an alternative. This new performance measure is based on the theory of zero-crossings of stochastic processes. We show that the derivative of a Gaussian is the optimal edge detector for this new measure.

Paper Details

Date Published: 1 June 1990
PDF: 9 pages
Proc. SPIE 1244, Image Processing Algorithms and Techniques, (1 June 1990); doi: 10.1117/12.19530
Show Author Affiliations
Hemant D. Tagare, Rice Univ. (United States)
Rui J. P. de Figueiredo, Rice Univ. (United States)


Published in SPIE Proceedings Vol. 1244:
Image Processing Algorithms and Techniques
Robert J. Moorhead; Keith S. Pennington, Editor(s)

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