Lightweight iris segmentation model based on multiscale feature and attention mechanism

HUO Guang, LIN Da-wei, LIU Yuan-ning, ZHU Xiao-dong, YUAN Meng, GAI Di

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J Jilin Univ Eng Tech Ed ›› 2023, Vol. 53 ›› Issue (09) : 2591-2600. DOI: 10.13229/j.cnki.jdxbgxb.20220044

Lightweight iris segmentation model based on multiscale feature and attention mechanism

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Abstract

Aiming at the problem that deep learning-based iris segmentation models need a large number of parameters， computation cost， and space occupation， a lightweight iris segmentation model is proposed in this paper. First， the feature extraction network of Linknet is replaced with the improved lightweight deep neural network MobileNetv3. This design significantly improves the efficiency of the model while maintaining accuracy. Then， in order to reduce the loss of iris feature information， a multiscale feature extraction module is designed in this paper. Once again， an efficient parallel attention mechanism is introduced to suppress noise interference and enhance the weight of iris region pixels. Finally， the proposed model was compared with other iris segmentation models on three iris databases， and the results showed that the model achieved a better balance between iris segmentation accuracy and efficiency.

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computer application / iris segmentation / deep learning / lightweight network / attention mechanism / multiscale feature

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HUO Guang , LIN Da-wei , LIU Yuan-ning , et al . Lightweight iris segmentation model based on multiscale feature and attention mechanism. Journal of Jilin University(Engineering and Technology Edition). 2023, 53(09): 2591-2600 https://doi.org/10.13229/j.cnki.jdxbgxb.20220044

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