Abstract
Eye localization plays a fundamental role in iris recognition, for it can define the effective regions used for iris recognition. This paper presents a new eye localization method based on light spots detection. First, images are preprocessed by Gaussian Smoothing Filter and dilation. Then, FAST feature detection algorithm is used to select candidate regions by detecting the light spots. Furthermore, we calculate the HOG features of these candidates and use the SVM classifier to obtain eye regions. If only one eye is localized, block matching algorithm is applied to fix the missed detection. The localization accuracy on two public dual-eye iris image databases, CASIA-IrisV4-Distance and MIR, keeps above 99.75%, and it shows that 98% of the samples have a normalized error value below 0.1, which demonstrates the success of the proposed method.
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This work is supported by research grants from Hangzhou Daishi Technology Co. Ltd, China.
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Zhang, Y., Chen, X., Chen, X., Zhou, D., Cao, E. (2017). An Eye Localization Method for Iris Recognition. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_45
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DOI: https://doi.org/10.1007/978-3-319-69923-3_45
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