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Proceedings Paper

Automatic selection of edge detector parameters based on spatial and statistical measures
Author(s): Raz Koresh; Yitzhak Yitzhaky
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Paper Abstract

The basic and widely used operation of edge detection in an image usually requires a prior step of setting the edge detector parameters (thresholds, blurring extent etc.). In real-world images this step is usually done subjectively by human observers. Finding the best detector parameters automatically is a problematic challenge because no absolute ground truth exists when real-world images are considered. However, the advantage of automatic processing over manual operations done by humans motivates the development of automatic detector parameter selection which will produce results agreeable by human observers. In this work we propose an automatic method for detector parameter selection which considers both, statistical correspondence of detection results produced from different detector parameters, and spatial correspondence between detected edge points, represented as saliency values. The method improves a recently developed technique that employs only statistical correspondence of detection results, and depends on the initial range of possible parameters. By incorporating saliency values in the statistical analysis, the detector parameters adaptively converge to best values. Automatic edge detection results show considerable improvement of the purely statistical method when a wrong initial parameter range is selected.

Paper Details

Date Published: 2 November 2004
PDF: 9 pages
Proc. SPIE 5558, Applications of Digital Image Processing XXVII, (2 November 2004); doi: 10.1117/12.560586
Show Author Affiliations
Raz Koresh, Ben-Gurion Univ. of the Negev (Israel)
Yitzhak Yitzhaky, Ben-Gurion Univ. of the Negev (Israel)


Published in SPIE Proceedings Vol. 5558:
Applications of Digital Image Processing XXVII
Andrew G. Tescher, Editor(s)

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