Abstract

Due to renewed interest in security, iris images have become a popular biometric alternative to fingerprints for human identification. However, there exist very few databases on which researchers can test iris recognition technology. We present a novel method to augment existing databases through iris image synthesis. A multiresolution technique known as reverse subdivision is used to capture the necessary characteristics from existing irises, which are then combined to form a new iris image. In order to improve the results, a set of heuristics to classify iris images is proposed. We analyze the performance of these heuristics and provide preliminary results of the iris synthesis method.

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This paper was originally published as a short paper in the Graphite 2005 Conference Proceedings. More details on the publication are available at the ACM Portal.

Iris Synthesis: a MultiResolution Approach

Additionally, the subject is covered in more detail in my thesis. Although Chapter 5 is dedicated to Iris Synthesis the entire thesis revolves around multiresolution and synthesis.

Synthesizing Techniques Based on Multiresolution

Results

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