Three-dimensional object recognition using wavelets for feature denoising

Sung-Soo Kim; Takis Kasparis; Guy A. Schiavone

doi:10.1117/12.241988

7 June 1996 Three-dimensional object recognition using wavelets for feature denoising

Sung-Soo Kim, Takis Kasparis, Guy A. Schiavone

Proceedings Volume 2750, Digital Signal Processing Technology; (1996) https://doi.org/10.1117/12.241988
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

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.

Citation Download Citation

Sung-Soo Kim, Takis Kasparis, and Guy A. Schiavone "Three-dimensional object recognition using wavelets for feature denoising", Proc. SPIE 2750, Digital Signal Processing Technology, (7 June 1996); https://doi.org/10.1117/12.241988

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