Technical Section: A multiresolution approach to iris synthesis
Computers and Graphics
Iris biometrics for embedded systems
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Synthetic on-line signature generation. Part I: Methodology and algorithms
Pattern Recognition
Standardised system for automatic remote evaluation of biometric algorithms
Computer Standards & Interfaces
Biometrics inspired watermarking based on a fractional dual tree complex wavelet transform
Future Generation Computer Systems
Computer Vision and Image Understanding
A novel hand reconstruction approach and its application to vulnerability assessment
Information Sciences: an International Journal
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The popularity of iris biometric has grown considerably over the past two to three 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 data bases, 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 to 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 data base of iris images. In this work, we describe a model-based method to generate iris images and evaluate the 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 the importance of various parameters involved in generating iris images