Title
Three-Dimensional Object Recognition Using Wavelets For Feature Denoising
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.
Publication Date
1-1-1996
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
2750
Number of Pages
180-190
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0029770162 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0029770162
STARS Citation
Kim, Sung Soo; Kasparis, Takis; and Schiavone, Guy A., "Three-Dimensional Object Recognition Using Wavelets For Feature Denoising" (1996). Scopus Export 1990s. 2354.
https://stars.library.ucf.edu/scopus1990/2354