Research on Iris Feature Extraction and Recognition Technology Based on Deep Learning

[1] Mach. IntelH. Proenca, S. Filipe, R. Santos, et al, The UBIRIS.v2: A database of visible wavelength iris images captured on-the-move and at-a-distance[J]. IEEE Trans. Pattern Anal, 2010, 32(8):1529–1535. Proenca Mach. IntelH. Filipe S. Santos R. , The UBIRIS.v2: A database of visible wavelength iris images captured on-the-move and at-a-distance[J] . IEEE Trans. Pattern Anal , 2010 , 32 ( 8 ): 1529 – 1535 . Search in Google Scholar

[2] Fawzi A, Samulowitz H, Turaga D, et al. Adaptive data augmentation for image classification[C].2016 IEEE International Conference on Image Processing (ICIP). IEEE,2016. Fawzi A Samulowitz H Turaga D Adaptive data augmentation for image classification[C] . 2016 IEEE International Conference on Image Processing (ICIP) . IEEE , 2016 . Search in Google Scholar

[3] Carl M , Goldberg R .Iris biometrics: from segmentation to template security[J].Computing reviews, 2013, 54(11):672–673. Carl M Goldberg R Iris biometrics: from segmentation to template security[J] . Computing reviews , 2013 , 54 ( 11 ): 672 – 673 . Search in Google Scholar

[4] Hu J, Shen L, Sun G. Squeeze-and-excitation networks; proceedings of the Proceedings of the IEEE conference on computer vision and pattern recognition, F, [C] Salt Lake City, UT, USA 2018. Hu J Shen L Sun G. Squeeze-and-excitation networks ; proceedings of the Proceedings of the IEEE conference on computer vision and pattern recognition, F , [C] Salt Lake City, UT, USA 2018 . Search in Google Scholar

[5] Ibrahim M T, Khan T M, Khan S A, et al. Iris localization using local histogram and other image statistics[J]. Optics & Lasers in Engineering, 2012, 50(5):645–654. Ibrahim M T Khan T M Khan S A Iris localization using local histogram and other image statistics[J] . Optics & Lasers in Engineering , 2012 , 50 ( 5 ): 645 – 654 . Search in Google Scholar

[6] Chen Y, Wu C, Wang Y. T-center: a novel feature extraction approach towards large-scale iris recognition [J]. IEEE Access, 2020, 8: 32365–32375. Chen Y Wu C Wang Y. T-center: a novel feature extraction approach towards large-scale iris recognition [J] . IEEE Access , 2020 , 8 : 32365 – 32375 . Search in Google Scholar

[7] Leonard Flom, Aran Safir. Iris recognition system [P]. United States Patent No. 46413491987. Flom Leonard Safir Aran Iris recognition system [P] . United States Patent No. 46413491987 . Search in Google Scholar

[8] Liu M, Zhou Z, Shang P, et al. Fuzzified image enhancement for deep learning in iris recognition [J]. IEEE Transactions on Fuzzy Systems, 2019, 28(1): 929. Liu M Zhou Z Shang P Fuzzified image enhancement for deep learning in iris recognition [J] . IEEE Transactions on Fuzzy Systems , 2019 , 28 ( 1 ): 929 . Search in Google Scholar

[9] Zhao Z, Kumar A. Towards more accurate iris recognition using deeply learned spatially corresponding features; proceedings of the Proceedings of the IEEE international conference on computer vision, F, [C] The Hong Kong Polytechnic University 2017. Zhao Z Kumar A. Towards more accurate iris recognition using deeply learned spatially corresponding features; proceedings of the Proceedings of the IEEE international conference on computer vision, F, [C] The Hong Kong Polytechnic University 2017 . Search in Google Scholar

[10] Nguyen K, Fookes C, Ross A, et al. Iris recognition with off-the-shelf CNN features: a deep learning perspective [J]. IEEE Access, 2017, 6: 18848–55. Nguyen K Fookes C Ross A Iris recognition with off-the-shelf CNN features: a deep learning perspective [J] . IEEE Access , 2017 , 6 : 18848 – 55 . Search in Google Scholar

[11] Lei Songze, Zhang Boxing, Wang Yanhong, et al. Object Recognition using Non-negative Matrix Factorization with Sparseness Constraint and Neural Network. information [J], 2019, 10(37):1–17(EI). Songze Lei Boxing Zhang Yanhong Wang Object Recognition using Non-negative Matrix Factorization with Sparseness Constraint and Neural Network . information [J] , 2019 , 10 ( 37 ): 1 – 17 (EI). Search in Google Scholar

[12] Othman N, Dorizzi B, Garcia-Salicetti S. OSIRIS: An open source iris recognition software [J]. Pattern Recognition Letters, 2016, 82: 124–31. Othman N Dorizzi B Garcia-Salicetti S. OSIRIS: An open source iris recognition software [J] . Pattern Recognition Letters , 2016 , 82 : 124 – 31 . Search in Google Scholar

[13] Raja K B , Raghavendra R , Vemuri V K , et al. Smartphone based visible iris recognition using deep sparse filtering[J]. Pattern Recognition Letters, 2015, 57:33–42. Raja K B Raghavendra R Vemuri V K Smartphone based visible iris recognition using deep sparse filtering[J] . Pattern Recognition Letters , 2015 , 57 : 33 – 42 . Search in Google Scholar

[14] Mengjia Wang, Research on iris recognition algorithm based on deep learning [D]. Jilin University, 2022. Wang Mengjia Research on iris recognition algorithm based on deep learning [D] . Jilin University , 2022 . Search in Google Scholar

[15] Qi Zhao, Research on Iris Recognition Algorithm Based on Deep Learning [D]. Xidian University, 2020. Zhao Qi Research on Iris Recognition Algorithm Based on Deep Learning [D] . Xidian University , 2020 . Search in Google Scholar

[16] Liu N, Zhang M, Li H, et al. Deepiris: Learning pairwise filter bank for heterogeneous iris verification [J]. Pattern Recognition Letters, 2016, 82: 154–61. Liu N Zhang M Li H Deepiris: Learning pairwise filter bank for heterogeneous iris verification [J] . Pattern Recognition Letters , 2016 , 82 : 154 – 61 . Search in Google Scholar

[17] Alinia Lat R, Danishvar S, Heravi H, et al. Boosting Iris Recognition by Margin-Based Loss Functions [J]. Algorithms, 2022, 15(4): 118. Alinia Lat R Danishvar S Heravi H Boosting Iris Recognition by Margin-Based Loss Functions [J] . Algorithms , 2022 , 15 ( 4 ): 118 . Search in Google Scholar

[18] Roy K, Bhattacharya P Iris recognition with support vector machines[J]. Lecture Notes in Science. 2006, 3832: 486–492. Roy K Bhattacharya P Iris recognition with support vector machines[J] . Lecture Notes in Science . 2006 , 3832 : 486 – 492 . Search in Google Scholar

[19] Gangwar A, Joshi A. DeepIrisNet: deep iris representation with applications in iris recognition and cross-sensor iris recognition; proceedings of the 2016 IEEE international conference on image processing (ICIP), F, [C]. IEEE 2016. Gangwar A Joshi A. DeepIrisNet: deep iris representation with applications in iris recognition and cross-sensor iris recognition; proceedings of the 2016 IEEE international conference on image processing (ICIP), F, [C] . IEEE 2016 . Search in Google Scholar