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Proceedings Paper

Orthogonal-function-based image filtering and edge detection
Author(s): Jun Shen; Wei Shen; Dan-Fei Shen
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Paper Abstract

Filtering and edge detection are widely used in image processing and computer vision. The following problems are important: computational complexity, precision, possibility to be realized in parallel, and detecting edges with a subpixel precision. By use of orthogonal polynomial theory, we propose in the present paper a new realization of image filters and their derivatives for edge detection, with a reduced and constant complexity and a good precision. In particular, we present the Hermite integration to realize Gaussian filters and the Laguerre integration for Shen-Castan filters. We show that the output of these filters can be calculated by the weighted sum of the signal values at positions determined by the roots of orthogonal polynomials. Generalization to M-D cases and to derivative calculation for edge detection, and the implementation in discrete cases are presented as well. Our method is implemented and tested for computer-generated and real images, the experimental results are satisfactory.

Paper Details

Date Published: 28 August 1995
PDF: 8 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217453
Show Author Affiliations
Jun Shen, Univ. de Bordeaux III (France)
Wei Shen, Poitiers Univ. (France)
Dan-Fei Shen, Univ. de Bordeaux I (France)

Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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