ICSNET: iris center localization and segmentation in non-cooperative environment with visible illumination

Jiangang Li; Xin Feng

doi:10.1117/12.2681132

23 May 2023 ICSNET: iris center localization and segmentation in non-cooperative environment with visible illumination

Jiangang Li, Xin Feng

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 1264507 (2023) https://doi.org/10.1117/12.2681132
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

Iris images captured in non-cooperative environments with visible illumination often suffer from adverse noise, which challenges many existing iris localization and segmentation methods. To address this problem, we propose a simple yet efficient anchor-free Iris Center localization and Segmentation Network, named ICSNet. Unlike existing methods that rely on post-processing on the segmented iris mask to fit the inner and outer circle, ICSNet provides an end-to-end iris localization and segmentation solution by explicitly considering the physiological characteristics of the iris. In ICSNet, an anchor-free center based double-circle iris localization network and an iris mask segmentation module are designed to directly detect the circle boundary of both pupil and iris and segment the iris region in an end-to-end framework. Extensive experiments on the challenging iris datasets (NICE-II) show that our ICSNet achieves excellent iris localization and segmentation performance. Especially, it achieves 84.02% box IoU and 89.15% mask IoU, and outperforms the state-of-the-art methods by nearly 3.8% and 1.65% respectively.

Citation Download Citation

Jiangang Li and Xin Feng "ICSNET: iris center localization and segmentation in non-cooperative environment with visible illumination", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 1264507 (23 May 2023); https://doi.org/10.1117/12.2681132

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