1 July 1990 Representation and recognition of 3-D curved objects using complete 3-D range data
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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.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ren C. Luo, Yong H. Kim, "Representation and recognition of 3-D curved objects using complete 3-D range data", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); doi: 10.1117/12.18896; https://doi.org/10.1117/12.18896
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