Exploring the Use of IrisCodes for Presentation Attack Detection
In this project, we investigate whether IrisCodes, that are commonly used for iris recognition, can be used for presentation attack detection. IrisCodes are binary phasor features extracted from the geometrically normalized iris, where the annular iris region is transformed to a rectangular entity. We demonstrate that including pupil information in IrisCodes improves presentation attack detection performance. Further, we demonstrate that extracting binary phasor information from the un-normalized iris image - referred to as OcularCode in this paper - can further boost the performance.
C. Chen and A. Ross, "Exploring the Use of IrisCodes for Presentation Attack Detection," Proc. of 9th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), (Los Angeles, USA), October 2018.
C. Chen and A. Ross, "A Multi-Task Convolutional Neural Network for Joint Iris Detection and Presentation Attack Detection," Proc. of IEEE Winter Conference on Applications of Computer Vision Workshops (WACVW), (Lake Tahoe, USA), March 2018.