On Generation and Analysis of Synthetic Iris Images

Jinyu Zuo, Natalia A. Schmid, Xiaohan Chen
2007 IEEE Transactions on Information Forensics and Security  
The popularity of iris biometric has grown considerably over the past 2-3 years. It has resulted in the development of a large number of new iris encoding and processing algorithms. Since there are no publicly available large scale and even medium size databases, neither of the newly designed algorithms has undergone extensive testing. The designers claim exclusively high recognition performance when the algorithms are tested on a small amount of data. In a large scale setting, systems are yet
more » ... o be tested. Since the issues of security and privacy slow down the speed of collecting and publishing iris data, an optional solution to the problem of algorithm testing is to synthetically generate a large scale database of iris images. In this work, we describe a model based method to generate iris images and evaluate performance of synthetic irises by using a traditional Gabor filter based iris recognition system. A comprehensive comparison of synthetic and real data is performed at three levels of processing: (1) image level, (2) texture level, and (3) decision level. A sensitivity analysis is performed to conclude on importance of various parameters involved in generating iris images.
doi:10.1109/tifs.2006.890305 fatcat:ayvjlgki4ze7tkntpg3hycgy6u