Research on face recognition method in working environment of coal preparation plant

The face image information of coal preparation plant is easily affected by complex environmental factors, which makes the recognition difficult. In order to solve this problem, a face recognition method in working environment of coal preparation plant is proposed. The Gabor wavelet transform is applied to the normalized original face image of coal preparation plant to obtain characteristic maps of 8 directions and 5 scales. The method encodes with the improved AR-LGC coding algorithm, and characteristic fusion is performed on the encoded maps of different directions at the same scale to obtain the fused characteristic map of the image. The fused characteristic map is divided into multiple sub-blocks, and the histogram characteristic vector H is obtained by counting the block histogram and weighting cascade. Then H is trained in residual neural network to realize the face recognition of the personnel in the coal preparation plant. The improved AR-LGC coding algorithm enhances the texture correlation of face im