A new iris recognition method based on PCA and sparse representation towards occlusion

Regarding the problem of iris recognition under occlusions which will greatly degrade the recognition results, this paper proposes a robust iris recognition method based on sparse representation and principal component analysis (PCA). The experimental results show that the correct recognition rate of the proposed method is encouraging. Moreover, the proposed method is robust to real occlusions or simulative occlusions. The experimental results on the CASIA iris database which is the largest publicly available iris image data sets show that the performance of the proposed method is encouraging and comparable to the best iris recognition algorithm found in the current literature.