12 April 2004 Invariant object recognition based on the generalized discrete radon transform
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Abstract
We introduce a method for classifying objects based on special cases of the generalized discrete Radon transform. We adjust the transform and the corresponding ridgelet transform by means of circular shifting and a singular value decomposition (SVD) to obtain a translation, rotation and scaling invariant set of feature vectors. We then use a back-propagation neural network to classify the input feature vectors. We conclude with experimental results and compare these with other invariant recognition methods.
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Glenn R. Easley, Glenn R. Easley, Flavia Colonna, Flavia Colonna, } "Invariant object recognition based on the generalized discrete radon transform", Proc. SPIE 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II, (12 April 2004); doi: 10.1117/12.541134; https://doi.org/10.1117/12.541134
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