Ali Reza Akoushideh

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Statistical texture features extraction algorithms can be classified into first, second, and higher order. The difference between these classes is that the first-order statistics estimate properties of individual image pixel values, while in the second and higher order statistics estimate properties of two or more image pixel values occurring at specific(More)
The most popular second-order statistical texture features are derived from the co-occurrence matrix, which has been proposed by Haralick. However, the computation of both matrix and extracting texture features are very time consuming. In order to improve the performance of co-occurrence matrices and texture feature extraction algorithms, we propose an(More)
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