Sign language recognition method based on deep learning

The invention discloses a sign language recognition method based on deep learning. The sign language recognition method based on deep learning comprises the steps that (1) database sample sets are divided; (2) image blocks are acquired; (3) data are whitened; (4) a sparse self-coding network is trained; (5) a convolution characteristic graph is obtained; (6) a pooling characteristic graph is obtained; (7) a classifier is trained; and (8) classification results are tested. The sparse self-coding network is trained by using a back propagation algorithm so that recognition rate is enhanced in processing of complex background data. The weight of the sparse self-coding network is selected to act as the convolution kernel, the convolution characteristic graph is obtained through convolution, and supervised learning and unsupervised learning are combined so that manpower and material resources of manual tag marking can be reduced. The pooling characteristic graph is obtained by adopting the maximum pooling method so that characteristic dimension can be reduced and complexity the sign language recognition task can be reduced.