Abstract
Iris identification (IRI) constitutes an increasingly accepted methodology of biometrics. IRI is based on the successful encoding and matching of distinctive iris features (folds, freckles etc.), which - in turn - presupposes that iris segmentation has been accurately performed. In contrast to the inner (iris/pupil) iris boundary, which – owing to the high contrast between the adjacent areas - is relatively easy to localize, detection of the outer (iris/sclera) iris boundary is more challenging since the low contrast between the separated areas often results in fragmented, ambiguous and spurious edges. A novel approach to iris boundary detection is presented here, featuring a genetic algorithm (GA) for outer iris boundary detection.
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Tambouratzis, T., Masouris, M. (2007). GA-Based Iris/Sclera Boundary Detection for Biometric Iris Identification. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4432. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71629-7_52
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DOI: https://doi.org/10.1007/978-3-540-71629-7_52
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