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Proceedings Paper

Error analysis for finding Deriche's optimum filters and 3D range images segmentation
Author(s): Mourad Djebali; Mahmound Melkemi; D. Vandorpe
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Paper Abstract

The analysis of three-dimensional (3D) scenes from range images needs robust and efficient methodology to recover exact and useful information. Different approaches for surface segmentation in range data are proposed, and the most interesting are the segmentation methods based on function approximation and local neighborhood properties such as curvatures. Our scheme is to deal with classification of each range pixel by the sign of Gaussian (K) and mean (H) curvatures into three (3) fundamental surface types: convex, concave, and plane. Since the derivation of H and K involves calculation of partial derivatives in the image, the KH-map is susceptible to noise. Therefore, we propose the use of DERICHE's optimum filters which give more precise results. The performance degree of these optimum filters depends strongly on the choice of the values of the parameter (alpha) . Using a matrix representation of DERICHE's recursive systems we also propose a theoretical error analysis which allows the determination of the best `range' of (alpha) 's values.

Paper Details

Date Published: 30 December 1994
PDF: 9 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196720
Show Author Affiliations
Mourad Djebali, Univ. Lyon I-Claude Benard (France)
Mahmound Melkemi, Univ. Lyon I-Claude Benard (France)
D. Vandorpe, Univ. Lyon I-Claude Benard (France)


Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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