Marana, Aparecido Nilceu [UNESP]da, L. [UNESP]Velastin, S. A. [UNESP]Lotufo, R. A. [UNESP]2014-05-272014-05-271997-01-01ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, v. 4, p. 2773-2775.0736-7791http://hdl.handle.net/11449/64992This paper presents a technique for oriented texture classification which is based on the Hough transform and Kohonen's neural network model. In this technique, oriented texture features are extracted from the Hough space by means of two distinct strategies. While the first operates on a non-uniformly sampled Hough space, the second concentrates on the peaks produced in the Hough space. The described technique gives good results for the classification of oriented textures, a common phenomenon in nature underlying an important class of images. Experimental results are presented to demonstrate the performance of the new technique in comparison, with an implemented technique based on Gabor filters.2773-2775engMathematical transformationsNeural networksHough transformKohonen's self organizing mapOriented texture classificationFeature extractionTrabalho apresentado em evento10.1109/ICASSP.1997.595364Acesso aberto2-s2.0-00307014246027713750942689