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12 April 2004 Invariant object recognition based on the generalized discrete radon transform
Glenn R. Easley, Flavia Colonna
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Proceedings Volume 5439, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks II; (2004) https://doi.org/10.1117/12.541134
Event: Defense and Security, 2004, Orlando, Florida, United States
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 and 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); https://doi.org/10.1117/12.541134
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Cited by 2 scholarly publications.
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KEYWORDS
Radon transform
Object recognition
Neural networks
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