Paper
30 December 1994 Error analysis for finding Deriche's optimum filters and 3D range images segmentation
Mourad Djebali, Mahmound Melkemi, D. Vandorpe
Author Affiliations +
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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mourad Djebali, Mahmound Melkemi, and D. Vandorpe "Error analysis for finding Deriche's optimum filters and 3D range images segmentation", Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); https://doi.org/10.1117/12.196720
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KEYWORDS
Image segmentation

Digital filtering

Error analysis

3D image processing

Image filtering

Calculus

Convolution

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