This paper presents an efficient technique for accurate detection of iris boundary, which is an important issue for any iris-based biometric identification system. Our proposed technique follows scaling, histogram equalization, edge detection and finally removal of unnecessary edges present in the eye image. Scaling and removing unnecessary edges enables us to reduce the search space for iris boundary. Experimental results show that with our approach it is possible to detect iris boundary as much as 98% of the eye images in CASIA database accurately and it needs only 25% time compared to the existing approaches. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Dey, S., & Samanta, D. (2007). Accurate iris boundary detection in iris-based biometrie authentication process. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4815 LNCS, pp. 600–607). https://doi.org/10.1007/978-3-540-77046-6_74
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