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Title

Range image segmentation using surface selection criterion

Author(s)

Bab-Hadiashar, Alireza;  Gheissari, Niloofar

Abstract

In this paper, we address the problem of recovering the true underlying model of a surface while performing the segmentation. First, and in order to solve the model selection problem, we introduce a novel criterion, which is based on minimising strain energy of fitted surfaces. We then evaluate its performance and compare it with many other existing model selection techniques. Using this criterion, we then present a robust range data segmentation algorithm capable of segmenting complex objects with planar and curved surfaces. The presented algorithm simultaneously identifies the type (order and geometric shape) of each surface and separates all the points that are part of that surface. This paper includes the segmentation results of a large collection of range images obtained from objects with planar and curved surfaces. The resulting segmentation algorithm successfully segments various possible types of curved objects. More importantly, the new technique is capable of detecting the association between separated parts of a surface, which has the same Cartesian equation while segmenting a scene. This aspect is very useful in some industrial applications of range data analysis.

Publication type

Journal article

Research centre

Swinburne University of Technology. Faculty of Engineering and Industrial Sciences

Source

IEEE Transactions on Image Processing, Vol. 15, no. 7 (Jul 2006), pp. 2006-2018

Publication year

2006

Keyword(s)

Model selection;  Range data;  Robust range data segmentation;  Scale estimation

Publisher

IEEE

ISSN

1057-7149

Publisher URL

http://dx.doi.org/10.1109/TIP.2006.877064

Copyright

Copyright © 2006 IEEE. Published version of the paper reproduced here in accordance with the copyright policy of the publisher. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Full text

Peer reviewed