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Granularity analysis is one of the most essential issues in authenticate. To improve the identification accuracy, a Deep Belief Network (DBN) based method is proposed in this paper. DBN can extract features from image samples automatically.4800 rock images from Ordos Basin are used in this paper, 1200 of them are used to test the model accuracy and the result achieves 94.75%. According to theoretical and actual data test, the method proposed in this paper is efficiency and accuracy.