Novel Study on An Efficient of Coal and Gangue Recognition Algorithm

Yang Li

Abstract


In order to automatically select the gangue, this study obtained the difference and distribution regularity of the grayscale distribution by analyzing a large number of image data. By improving the multiple kernel Fisher discriminant analysis method, its approach is that the original training set is splited into a number of small sample sets, which in turn calculate projection mapping by using” voting strategy” discrimination for the samples. The experiments for face recognition show that the multiple kernel Fisher algorithm based on the diversity samples can improve the computing speed without reduction of classification correct rate.


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