Laser & Optoelectronics Progress, Volume. 59, Issue 4, 0410006(2022)
Heterogeneous Noise Iris Segmentation Based on Attention Mechanism and Dense Multiscale Features
Figures & Tables(16)
Fig. 1. Examples of eye image acquisition in complex scenes. (a) Gaze deviation; (b) absence of iris; (c) eyelash occlusion; (d) iris rotation; (e) blur; (f) hair shade; (g) specular reflection; (h) glasses occlusion
Fig. 8. Curves of training loss function and precision change at different datasets. (a) CASIA; (b) UBIRIS; (c) MICHE
Fig. 9. Segmentation results of different methods on MICHE dataset. (a) Original image; (b) ground truth; (c) results of Deeplab V3; (d) results of U-Net; (e) results of RTV-L; (f) results of PI-Unet; (g) results of MFFIris-Unet
Fig. 10. Segmentation results of different methods on CASIA dataset. (a) Original image; (b) ground truth; (c) results of Deeplab V3; (d) results of U-Net; (e) results of RTV-L; (f) results of PI-Unet; (g) results of MFFIris-Unet
Fig. 11. Segmentation results of different methods on UBIRIS dataset. (a) Original image; (b) ground truth; (c) results of Deeplab V3; (d) results of U-Net; (e) results of RTV-L; (f) results of PI-Unet; (g) results of MFFIris-Unet
Fig. 13. Visualized results predicted by the base model and MFFIris-Unet. (a) Original image; (b) ground truth; (c) results of base method; (d) results of MFFIris-Unet
Table 1. Evaluation index results of different methods on three iris datasets
View tableTable 1. Evaluation index results of different methods on three iris datasets
Method Dataset R P F1-Score mIoU /% Average time /s μ /% σ /% μ /% σ /% μ /% σ /% Deeplab V3 CASIA 90.13 6.62 92.80 4.12 93.21 3.67 88.21 0.56 UBIRIS 85.17 9.53 90.92 4.01 87.55 6.32 79.24 0.44 MICHE 89.84 10.93 91.66 8.12 91.18 8.89 84.69 0.41 U-Net CASIA 91.77 7.62 95.23 3.51 91.78 5.58 87.34 0.93 UBIRIS 91.96 7.82 90.29 4.63 90.81 4.92 81.92 0.67 MICHE 88.86 13.13 90.75 8.56 88.25 10.52 81.20 0.66 RTV-L CASIA 80.95 6.59 95.83 3.91 87.55 4.58 78.11 2.68 UBIRIS 88.23 9.66 85.16 10.58 85.97 8.72 74.01 1.15 MICHE 84.56 17.61 74.27 16.82 77.10 14.71 64.21 1.57 PI-Unet CASIA 93.11 8.69 95.22 5.31 96.53 5.41 94.21 0.18 UBIRIS 91.87 7.43 91.98 4.55 95.25 6.25 92.31 0.26 MICHE 93.52 10.11 93.65 9.16 94.02 8.52 93.53 0.33 MFFIris-Unet CASIA 92.62 7.65 96.56 3.69 97.14 4.36 94.61 0.11 UBIRIS 92.87 6.87 92.96 3.68 96.59 4.11 94.28 0.10 MICHE 94.05 10.21 93.14 8.69 96.54 8.62 93.63 0.07
Table 2. Comparison of the number of parameters, computation amount, and storage space of different methods
View tableTable 2. Comparison of the number of parameters, computation amount, and storage space of different methods
Method Params /106 FLOPs /109 Storage space /GB FCN8s 134.27 84.99 0.513 U-Net 26.36 62.61 0.121 SegNet 16.31 53.93 0.123 Deeplab V3 18.86 26.29 0.072 PI-Unet 2.86 1.56 0.012 MFFIris-Unet 1.45 0.35 0.005
Table 3. Results of ablation experiments
View tableTable 3. Results of ablation experiments
Method Dataset F1-Score /% mIoU /% Average time /s Train time /h Model size /MB Base CASIA 96.95 94.40 0.76 6 9.69 UBIRIS 96.23 93.61 0.61 22 MICHE 96.47 93.51 0.55 23 Base+RBU+Atten CASIA 96.56 93.85 0.22 3 5.32 UBIRIS 95.22 93.44 0.16 8 MICHE 95.62 93.21 0.13 5 Base+RBU+FPM CASIA 96.89 94.59 0.12 5.5 5.66 UBIRIS 96.29 93.96 0.08 21 MICHE 96.54 93.69 0.10 22 MFFIris-Unet CASIA 97.14 94.61 0.11 3 5.66 UBIRIS 96.59 94.28 0.07 8 MICHE 96.54 93.63 0.10 5
Tools
Get Citation
Copy Citation Text
Xuanang You, Peng Zhao, Xiaodong Mu, Kun Bai, Sai Lian. Heterogeneous Noise Iris Segmentation Based on Attention Mechanism and Dense Multiscale Features[J]. Laser & Optoelectronics Progress, 2022, 59(4): 0410006
Paper Information
Category: Image Processing
Received: Jan. 27, 2021
Accepted: Mar. 25, 2021
Published Online: Jan. 25, 2022
The Author Email: You Xuanang (youxuanang@163.com), Zhao Peng (zpxhh@163.com)
© Copyright 2018-2021 | Chinese Laser Press.
All Rights Reserved 沪ICP备15018463号-20