1 March 1998 Three-dimensional object recognitions from two-dimensional images using wavelet transforms and neural networks
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Optical Engineering, 37(3), (1998). doi:10.1117/1.601908
Abstract
Three-dimensional object classification from 2-D IR images is shown. The wavelet transform is used for edge detection. Edge tracking is used for removing noise effectively in the wavelet transform. The invariant Fourier descriptor is used to describe the contour curves. Invariance under out-of-plane rotation is achieved by the feature space trajectory neural network working as a classifier.
Sylvain Deschenes, Yunlong Sheng, Paul C. Chevrette, "Three-dimensional object recognitions from two-dimensional images using wavelet transforms and neural networks," Optical Engineering 37(3), (1 March 1998). https://doi.org/10.1117/1.601908
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