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Proceedings Paper

Robust method of edge detection
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Paper Abstract

We present here the theory of developing robust test statistics for edge shape matching in one dimensional signals. We show that an unbiased test can be developed under the assumption of uncorrelated noise and this test can be made optimal and robust to perturbations of the assumed noise distribution under the extra assumption of symmetric noise. This approach to edge detection is believed to overcome the shortcomings of the uncertainty principle in image processing and is appropriate for use when edges of a certain type have to be identified with great accuracy in their location.

Paper Details

Date Published: 1 March 1992
PDF: 15 pages
Proc. SPIE 1708, Applications of Artificial Intelligence X: Machine Vision and Robotics, (1 March 1992); doi: 10.1117/12.58578
Show Author Affiliations
Maria Petrou, Univ. of Surrey (United Kingdom)
Josef Kittler, Univ. of Surrey (United Kingdom)


Published in SPIE Proceedings Vol. 1708:
Applications of Artificial Intelligence X: Machine Vision and Robotics
Kevin W. Bowyer, Editor(s)

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