Abstract
This paper proposes a new and original fuzzy approach to circular iris segmentation based on isolines, sine law and lookup tables. All isolines found in the eye image together form the space in which the inner and outer boundaries of the iris are searched for, while the sine law is used for identifying clusters of concyclic points within any given and possibly noisy isoline. The new segmentation procedure proved a failure rate of 5.83% when tested on 116,564 eye images (LG2200 subset of ND-CrossSenssor-Iris-2013 database) at an average speed of four images per second on a single Xeon L5420 core.
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This work was supported by the Applied Computer Science Laboratory (Bucharest, Romania).
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Popescu Bodorin, N., Balas, V.E., Penariu, P.S. (2018). Circular Fuzzy Iris Segmentation Using Isolines, Sine Law and Lookup Tables. In: Balas, V., Jain, L., Balas, M. (eds) Soft Computing Applications. SOFA 2016. Advances in Intelligent Systems and Computing, vol 634. Springer, Cham. https://doi.org/10.1007/978-3-319-62524-9_33
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DOI: https://doi.org/10.1007/978-3-319-62524-9_33
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