Popularity of iris biometric grew considerably over the past 2-3 years. It resulted in 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 algorithms has undergone extensive testing. With the lack of data, two major solutions to the problem of algorithm testing are possible: (i) physically collecting a large number of iris images or (ii) synthetically generating a large scale database of iris images. In this work, we describe a model based/anatomy based method to synthesize iris images and evaluate the performance of synthetic irises by using a traditional Gabor filter based system and by comparing local independent components extracted from synthetic iris images with those from real iris images. The issue of security and privacy is another argument in favor of generation of synthetic data. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Zuo, J., & Schmid, N. A. (2006). A model based, anatomy based method for synthesizing iris images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3832 LNCS, pp. 428–435). https://doi.org/10.1007/11608288_57
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