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Proceedings Paper

Blob tracking technique to range image segmentation
Author(s): Ivan D'Cunha; Nicolas Alvertos
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Paper Abstract

A robust segmentation scheme is one of the primary requirements for three-dimensional object recognition. The task of partitioning a given image into homogeneous regions has been the centerpiece of investigations of several major researchers all of these years. In this paper we propose a simplistic range image segmentation scheme for un-occluded cluttered three- dimensional objects in a scene. An assumption relating to the three-dimensional objects being quadric in nature, would further enable us to demonstrate an object recognition scheme which has been proposed in an earlier publication. The proposed method involves the extraction of jump edges which we refer to as global edges. After having median filtered the resultant image, a thinning algorithm is implemented which is subsequently followed by the blob determination algorithm thereby completing the segmentation process. Experiments have been conducted on range images of scenes consisting of several quadric surfaces with promising results. Application of the object recognition scheme subsequently successfully classified most of the objects in the scenes as either spherical, cylindrical, or planar in nature.

Paper Details

Date Published: 10 October 1994
PDF: 8 pages
Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, (10 October 1994); doi: 10.1117/12.188894
Show Author Affiliations
Ivan D'Cunha, Old Dominion Univ. (United States)
Nicolas Alvertos, Univ. of Crete (Greece)


Published in SPIE Proceedings Vol. 2353:
Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision
David P. Casasent, Editor(s)

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