Palmprint recognition based on deep learning

Deep learning method has been considered as a breakthrough in computer vision, successfully aplied in many domains, including biometrics. Palmprint recognition has been accepted with high acceptability and low intrusion. In this study, deep learning was introduced into palmprint recognition for a better performance. Three concrete steps were involved in the application. First, a deep belief net was built by top-to-down unsupervised training with training samples. Second, the optimum parameters were chosen to adapt the model for a robust performance. Third, the testing samples were labeled by employing the deep learning models. Compared with traditional recognition methods, such as PCA, LBP, the experimental results show that deep learning method has a higher recognition rate for palmprint recognition.