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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