Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/3062
Title: Three-dimensional object recognition using wavelets for feature denoising
Authors: Kasparis, Takis 
Kim, Sung Soo 
Schiavone, Guy A. 
metadata.dc.contributor.other: Κασπαρής, Τάκης
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Pattern recognition;Computer vision;Three-dimensional imaging
Issue Date: 7-Jun-1996
Source: The International Society for Optical Engineering, 1996, vol. 2750, pp. 180-190
Conference: SPIE Conference Proceedings 
Abstract: Recognition of 3D objects independent of size, position, and rotation is an important and difficult subject in computer vision. A 3D feature extraction method referred to as the Open Ball Operator (OBO) is proposed as an approach to solving the 3D object recognition problem. The OBO feature extraction method has the three characteristics of invariance to rotation, scaling, and translation invariance. Additionally, the OBO is capable of distinguishing between convexities and concavities in the surface of 3D object. The OBO also exhibits a good robustness to noise and uncertainty caused by inaccuracies in 3D measurements. A wavelet de- noising method is used for filtering out noise contained in the feature vectors of 3D objects.
ISBN: 0819421316
DOI: 10.1117/12.241988
Rights: © 1996 SPIE
Type: Conference Papers
Affiliation: University of Central Florida 
Affiliation : University of Central Florida 
Publication Type: Peer Reviewed
Appears in Collections:Κεφάλαια βιβλίων/Book chapters

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