3-DIMENSIONAL OBJECT RECOGNITION FROM 2-DIMENSIONAL IMAGES USING WAVELET TRANSFORMS AND NEURAL NETWORKS

Authors
DESCHENES S SHENG YL CHEVRETTE PC
Citation
S. Deschenes et al., 3-DIMENSIONAL OBJECT RECOGNITION FROM 2-DIMENSIONAL IMAGES USING WAVELET TRANSFORMS AND NEURAL NETWORKS, Optical engineering, 37(3), 1998, pp. 763-770
Citations number
17
Categorie Soggetti
Optics
Journal title
Optical engineering → ACNP
ISSN journal
00913286
Volume
37
Issue
3
Year of publication
1998
Pages
763 - 770
Database
ISI
SICI code
0091-3286(1998)37:3<763:3ORF2I>2.0.ZU;2-Y
Abstract
Three-dimensional object classification from 2-D IR images is shown. T he wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively in the wavelet transform. The invarian t Fourier descriptor is used to describe the contour curves. Invarianc e under out-of-plane rotation is achieved by the feature space traject ory neural network working as a classifier. (C) 1998 Society of Photo- Optical Instrumentation Engineers. [S0091-3286(98)01203-3].