Abstract
Iris localization is the prerequisite for the precise iris recognition. Compared with near-infrared iris images, the visible spectral iris images may have more fuzzy boundaries, which impair the iris detection. We can use multiple color components of different color spaces to realize the visible spectral iris localization. Firstly, the sclera is segmented and eyelids are located on \( \alpha \) component image through contrast adjustment and polynomial fitting. Secondly, morphological processing and CHT (Circular Hough Transform) is applied to localize the limbic boundary on R component image. Similarly, the pupillary boundary is localized on R component image and \( \alpha \) component image. Experimental results on visible spectral iris image dataset indicate that the proposed method has good performance on iris localization.
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Acknowledgments
This work is supported by National Science Foundation of China (No.60905012, 60572058) and International Fund of Beijing Institute of Technology.
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Wang, X., He, Y., Pei, K., Liang, M., He, J. (2016). Combining Multiple Color Components for Efficient Visible Spectral Iris Localization. In: You, Z., et al. Biometric Recognition. CCBR 2016. Lecture Notes in Computer Science(), vol 9967. Springer, Cham. https://doi.org/10.1007/978-3-319-46654-5_40
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DOI: https://doi.org/10.1007/978-3-319-46654-5_40
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