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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