Robust edge extraction for Swissranger SR-3000 range images

Authors:
Cang Ye;GuruPrasad M. Hegde
Affiliations:
Department of Applied Science, University of Arkansas, Little Rock, AR;Department of Applied Science, University of Arkansas, Little Rock, AR
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

This paper presents a new method for extracting object edges from range images obtained by a 3D range imaging sensor--the SwissRanger SR-3000. In range image preprocessing stage, the method enhances object edges by using surface normal information; and it employs the Hough Transform to detect straight line features in the Normal-Enhanced Range Image (NERI). Due to the noise in the sensor's range data, a NERI contains corrupted object surfaces that may result in unwanted edges and greatly encumber the extraction of linear features. To alleviate this problem, a Singular Value Decomposition (SVD) filter is developed to smooth object surfaces. The efficacy of the edge extraction method is validated by experiments in various environments.