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Proceedings Paper

Representation and recognition of 3-D curved objects using complete 3-D range data
Author(s): Ren C. Luo; Yong H. Kim
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Paper Abstract

This paper proposes a method to describe and identify 3-D curved objects using a complete set of 3-D range data. Curved 3-D objects in general are difficult to represent and identify because they lack distinct local properties such as edges planes cylindrical surfaces etc. which are the basic building blocks used to represent objects when using intensity or 2-D range images. In this paper we propose to use principal axes to establish a reference for describing a 3-D object. A method of obtaining an inertia matrix from the complete 3-D range data is developed. Using this method an unique set of principal axes of an object with an arbitrary 3-D position and orientation is first obtained. On the principal axis coordinate the object is described by the normalized features describing the shape of the object such as a spine compactness section size section contraction and section orientation. As experiments several 3-D objects are described using the proposed method by features two scalars and three vectors. For the purpose of identification a similarity measure between the two objects are defined based on the descriptions of objects. As the proposed method is based on the global features of objects using sufficient information from 3-D range data it provides an unique description which is suggestive of the shape of an object as well as an accurate noise-insensitive identifying method. 1.

Paper Details

Date Published: 1 July 1990
PDF: 12 pages
Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18896
Show Author Affiliations
Ren C. Luo, North Carolina State Univ. (United States)
Yong H. Kim, North Carolina State Univ. (United States)


Published in SPIE Proceedings Vol. 1233:
Medical Imaging IV: Image Processing
Murray H. Loew, Editor(s)

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