Finger Vein Recognition System Work Process
Keywords:
fingerprint vein pattern, biometric identification
Abstract
Finger vein identification is a biometric authentication method that shows great promise because of its distinct features, which include high accuracy, resilience, and non-invasiveness. This study offers a thorough analysis of the developments, approaches, and difficulties in the field of finger vein identification. An introduction of the fundamental ideas behind finger vein identification is given at the outset, along with information on the structure of finger veins and the imaging methods used to record vein patterns. It then goes into the many methods and algorithms used in finger vein identification systems for matching, classifying, and extracting features. The report also discusses new developments in finger vein identification technologies, including multimodal biometric systems that combine finger veins with other biometric modalities and deep learning-based techniques.The main difficulties that finger vein identification systems encounter are also covered in this work, including differences within the same class, environmental influences, and security issues. It also looks at possible uses for finger vein recognition in a variety of industries, including banking, healthcare, and access control. The study ends with some suggestions for future research and possible ways to get around some of the current problems to speed up the creation of more durable and trustworthy finger vein detection devices.
References
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2. Yunyun, Pan; Yi, Zhuo; Zhiwei, Chen; Zhen, Qiu; Yaobin, Mao (2019). [IEEE 2019 Chinese Control And Decision Conference (CCDC) - Nanchang, China (2019.6.3-2019.6.5)] 2019 Chinese Control And Decision Conference (CCDC) - Finger vein recognition based on Hessian-Affine operator. 5722–5727. doi:10.1109/ccdc.2019.8832770
3. Xiong, Zhangxi; Liu, Mingliang; Guo, Qing (2019). [IEEE 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) - Dalian, China (2019.3.29-2019.3.31)] 2019 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA) - Finger Vein Recognition Method Based on Center-Symmetric Local Binary Pattern. , (), 262–266. doi:10.1109/icaica.2019.8873475.
4. Sudhagar, D., Saturi, S., Choudhary, M., Senthilkumaran, P., Howard, E., Yalawar, M. S., & Vidhya, R. G. (2024). Revolutionizing data transmission efficiency in IoT-enabled smart cities: A novel optimization-centric approach. International Research Journal of Multidisciplinary Scope (IRJMS), 5(4), 592-602. https://doi.org/10.47857/irjms.2024.v05i04.01113.
5. Chen, Qing; Yang, Lu; Yang, Gongping; Yin, Yilong; Meng, Xianjing (2017). [IEEE ICASSP 2017 - 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - New Orleans, LA, USA (2017.3.5-2017.3.9)] 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - DFVR: Deformable finger vein recognition. , (), 1278–1282. doi:10.1109/ICASSP.2017.7952362
6. D. Akila;S.Jeyalaksshmi;R. Jayakarthik;S. Mathivilasini;G. Suseendran; (2021). Biometric Authentication With Finger Vein Images Based On Quadrature Discriminant Analysis . 2021 2nd International Conference on Computation, Automation and Knowledge Management (ICCAKM), (), –. doi:10.1109/iccakm50778.2021.9357705
7. RaunakBhupal;Kalidindi Lakshmi Sanjana;NikhilKishanKhaneja;PrakharBhartiya;AchaladiSpoorthiBhat;Sandesh B J; (2021). Finger Vein Authentication System . 2021 International Conference on Computer Communication and Informatics (ICCCI), (), –. doi:10.1109/iccci50826.2021.9402594
8. YufanZhang;Zhiping Liu; (2020). Research on Finger Vein Recognition Based on Sub-Convolutional Neural Network . 2020 International Conference on Computer Network, Electronic and Automation (ICCNEA), (), –. doi:10.1109/ICCNEA50255.2020.00051
9. Zhu, Chaoping; Yang, Yongbin; Jang, Yun (2019). [IEEE 2019 14th International Conference on Computer Science & Education (ICCSE) - Toronto, ON, Canada (2019.8.19-2019.8.21)] 2019 14th International Conference on Computer Science & Education (ICCSE) - Research on Denoising of Finger Vein Image Based on Deep Convolutional Neural Network. , (), 374–378. doi:10.1109/ICCSE.2019.8845517
10. Wu, Jiacun; He, Dongzhi (2018). [IEEE 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Chongqing (2018.6.27-2018.6.29)] 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC) - Finger Vein Recognition Based on Feature Point Distance. , (), 163–167. doi:10.1109/icivc.2018.8492806
11. Guo and Bing qiao ,Research on The Finger Vein Image Capture and Finger Edge Extraction Qingchang Yichang Testing Technology Research Institute Yichang, Hubei Province, China fingervein@126.com &fingervein@126.com
12. Georg Wimmer;BernhardPrommegger;AndreasUhl; (2021). Finger Vein Recognition and Intra-Subject Similarity Evaluation of Finger Veins using the CNN Triplet Loss . 2020 25th International Conference on Pattern Recognition (ICPR), (), –. doi:10.1109/icpr48806.2021.9413060
13. Chen, Guanghua; Dai, Qinghua; Tang, Xiao; Xu, Zihao (2018). [IEEE 2018 5th International Conference on Systems and Informatics (ICSAI) - Nanjing, China (2018.11.10-2018.11.12)] 2018 5th International Conference on Systems and Informatics (ICSAI) - An Improved Least Trimmed Square Hausdorff Distance Finger Vein Recognition. , (), 939–943. doi:10.1109/ICSAI.2018.8599439
14. Mei, Xiao; Ma, Hui (2019). [IEEE 2019 International Conference on Information Technology and Computer Application (ITCA) - Guangzhou, China (2019.12.20-2019.12.22)] 2019 International Conference on Information Technology and Computer Application (ITCA) - Finger vein recognition algorithm based on improved weighted sparse representation. , (), 6–8. doi:10.1109/ITCA49981.2019.00009
15. Vasilopoulos, Christos; Skodras, Athanassios (2018). [IEEE 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP) - Aristi Village, Zagorochoria, Greece (2018.6.10-2018.6.12)] 2018 IEEE 13th Image, Video, and Multidimensional Signal Processing Workshop (IVMSP) - A Novel Finger Vein Recognition System Based on Enhanced Maximum Curvature Points. , (), 1–5. doi:10.1109/ IVMSPW. 2018.8448746
16. ZejunZhang;FeiZhong;Wenxiong Kang; (2021). Study on Reflection-Based Imaging Finger Vein Recognition . IEEE Transactions on Information Forensics and Security, (), –. doi:10.1109/tifs.2021.3093791
17. Yang, Xiaofei; Yang, Chunhua; Yao, Zhijun (2016). [IEEE 2016 8th International Conference on Wireless Communications & Signal Processing (WCSP) - Yangzhou, China (2016.10.13-2016.10.15)] 2016 8th International Conference on Wireless Communications & Signal Processing (WCSP) - The finger vein recognition based on shearlet. , (), 1–5. doi:10.1109/wcsp.2016.7752499
18. P. S. Solanki, Y. B. Adhyaru and M. Choudhary, "EHSM - Heartbeat Sensors & Machine Learning for Horse Health Monitoring," 2024 Parul International Conference on Engineering and Technology (PICET), Vadodara, India, 2024, pp. 1-6, doi: 10.1109/PICET60765.2024.10716092
19. Prabakaran, P., Choudhary, M., Kumar, K., Loganathan, G. B., Salih, I. H., Kumari, K., & Karthick, L. (2024). Integrating Mechanical Systems With Biological Inspiration: Implementing Sensory Gating in Artificial Vision. In S. Padhi (Ed.), Trends and Applications in Mechanical Engineering, Composite Materials and Smart Manufacturing (pp. 193-206). IGI Global Scientific Publishing. https://doi.org/10.4018/979-8-3693-1966-6.ch012.
Published
2024-09-30
How to Cite
Atul Panchal, Aafrin Manknojiya, Jeel Bhatt, & Vivek Dave. (2024). Finger Vein Recognition System Work Process. Revista Electronica De Veterinaria, 25(2), 1537-1541. https://doi.org/10.69980/redvet.v25i2.1883
Section
Articles
