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Proceedings Paper

Extraction of edge-based and region-based features for object recognition
Author(s): Benjamin Coutts; Srinivas Ravi; Gongzhu Hu; Neelima Shrikhande
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Paper Abstract

One of the central problems of computer vision is object recognition. A catalogue of model objects is described as a set of features such as edges and surfaces. The same features are extracted from the scene and matched against the models for object recognition. Edges and surfaces extracted from the scenes are often noisy and imperfect. In this paper algorithms are described for improving low level edge and surface features. Existing edge extraction algorithms are applied to the intensity image to obtain edge features. Initial edges are traced by following directions of the current contour. These are improved by using corresponding depth and intensity information for decision making at branch points. Surface fitting routines are applied to the range image to obtain planar surface patches. An algorithm of region growing is developed that starts with a coarse segmentation and uses quadric surface fitting to iteratively merge adjacent regions into quadric surfaces based on approximate orthogonal distance regression. Surface information obtained is returned to the edge extraction routine to detect and remove fake edges. This process repeats until no more merging or edge improvement can take place. Both synthetic (with Gaussian noise) and real images containing multiple object scenes have been tested using the merging criteria. Results appeared quite encouraging.

Paper Details

Date Published: 20 August 1993
PDF: 9 pages
Proc. SPIE 2055, Intelligent Robots and Computer Vision XII: Algorithms and Techniques, (20 August 1993); doi: 10.1117/12.150183
Show Author Affiliations
Benjamin Coutts, Central Michigan Univ. (United States)
Srinivas Ravi, Central Michigan Univ. (United States)
Gongzhu Hu, Central Michigan Univ. (United States)
Neelima Shrikhande, Central Michigan Univ. (United States)

Published in SPIE Proceedings Vol. 2055:
Intelligent Robots and Computer Vision XII: Algorithms and Techniques
David P. Casasent, Editor(s)

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