2D Log gabor and SVD based parallel texture feature extraction usingNVIDIA GPU
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Texture feature is one of the most popular technique in image segmentation, classification, retrieval and many others. Now a days, among other ways of texture feature extraction, Gabor filtering has been widely used. Here, we are presenting a well ordered two dimensional texture feature extraction method. First, we convert the image to gray level. Then a 2D Log Gabor filter with different frequencies decomposed with the SVD algorithm applies on each converted part of gray level image to extract appropriate distinctive texture information. To evaluate the performance of proposed model, we utilize singular values of SVD as a feature vector. For classifier, we use Naïve Bayes classifier for training and testing our experimental dataset. In our experimental set up we utilize an NVDIA GeForce GTX780 graphics card. Experimental result showed this parallel implementation of our model is56X faster than conventional CPU implementation.