Rotation independent iris recognition by the rotation spreading neural network
Hironobu Takano, Kiyomi Nakamura · 2009
We proposed a iris recognition system using the rotation spreading neural network (R-SAN net). The R-SAN net correctly recognized the orientation of iris images using the iris pattern alone, not the positional arrangement of respective face parts. The orientation recognition performance of R-SAN net allows the accurate compensation of the orientation variation. For the characteristics of the iris pattern recognition, the equal error rate was 0.79%, which was investigated with iris images acquired from 19 subjects. On the other hand, the liveness detection method using a variation in the brightness of an iris pattern induced by a pupillary reflex was developed. The live and artificial irises were classified by a decision threshold of 3.7% brightness variation rate.