การประเมินรูปแบบของเส้นเลือดดำบริเวณแขนเพื่อใช้ในการพิสูจน์เอกลักษณ์บุคคล
Main Article Content
Abstract
Nowadays, the personal identification plays a very important role in a wide variety of fields, including financial business, office security, criminal investigation and forensic science. This study aims to evaluate the patterns of arm vein patterns for personal identification. Veinviewer®, a near-infrared vein visualization device, was applied in this study to illuminate the vein patterns in the arm of patients. The vein patterns were captured from one hundred twenty volunteers from their upper extremity, two shots at different times of not less than 1 month. The image data of their vein patterns were performed and analyzed by pixel to pixel mapping for the comparison. The comparing results showed the similarity rate of same people and the distinction rate between different people are in the range of 69.48 to 95.33 % and 1.47 to 84.43 %, respectively. The threshold of mapping accuracy was defined at 70.03 %. The false rejection rate (FRR) and false acceptation rate (FAR) were between 69.48 and 95.33 %, 1.47 and 84.43 %, respectively. Conclusively, it should be noted that the arm vein pattern technique is significantly effective for personal identification.
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References
[2] Wu, J.D. and Liu, C.T., 2011, Finger-vein pattern identification using principal component analysis and the neural network technique, Exp. Syst. Appl. 38: 5423-5427.
[3] Ain, A., Hong, L. and Pankanti, S., 2000, Biometric identification, Commun. ACM. 43(2): 90-98.
[4] Wiangsamut, S., 2001, Identification by biometrics, J. Sci. Technol. MSU. 31: 426-431. (in Thai)
[5] Mercy, B.E. and Nwachukwu, E., 2015, An efficient image preprocessing in an improved intelligent multi biometric authentication system, Int. J. Appl. Infrom. Sys. 9: 37-42.
[6] Liu, C.H., Wang, J.S., Peng, C.C. and Shyu, J.Z., 2015, Evaluating and selecting the biometrics in network security, Secur. Commun. Networks 8: 727-739.
[7] Kim, H.J., 1995, Biometrics, is it a viable proposition for identity authentication and access control?, Comp. Secur. 14: 205-214.
[8] Analysis of Palm Vein Biometric System, 2007, Available Source: https://courses.ece.ubc.ca/cpen442/term_project/reports/2007-fall/Analysis_of_Palm_Vein_Biome tric.pdf, April 9, 2018.
[9] Wang, L., Leedham, G. and Siu-Yeung Cho, D., 2008, Minutiae feature analysis for infrared hand vein pattern biometrics, Pattern Recognition 41: 920-929.
[10] Basavatia, A., Fret, J., Lukaj, A., Kuo, H., Yaparpalvi, R., Tome, W.A. and Kalnicki, S., 2016, Right care for the right patient each and every time, Cureus 8(2): e492.
[11] Im, S.K., Park, H.M., Kim, Y.W., Han, S.C., Kim, S.W. and Kang, C.H., 2011, An biometric identification system by extracting hand vein patterns, J. Korean Phys. Soc. 38: 268-272.
[12] Wong, K., Lai, T., Lee, B. and Shum, F., 2007, Analysis of Palm Vein Biometric System, Available Source: https://courses.ece.ubc.ca/412/term_project/reports/2007, March 8, 2018.
[13] Shahin, M., Badawi, A. and Kamel, M., 2007, Biometric authentication using fast correlation of near infrared hand vein patterns, Int. J. Biol. Med. Sci. 2: 141-148.
[14] Gnee, N.S., 2009, A study of hand vein, neck vein and arm vein extraction for authentication, pp.949-952, 7th International Conference on Information, Communications and Signal Processing (ICICS).
[15] Deepamalar, M. and Madheswaran, M., 2010, An improved multimodal palm vein recognition system using shape and texture features, Int. J. Comp. Theor. Eng. 2: 436-444.
[16] Soni, M., Gupta, S., Rao, M. and Gupta, P., 2010, A new vein pattern-based verification system, Int. J. Comp. Sci. Inform. Secur. 8: 58-63.
[17] Beg, K.R., Saiswani, A., Vhadalure, M., Shirke, A. and Jaokar, S., 2012, Vein structure authentication system, pp. 15-18., IJCA Proceedings on National Conference on Recent Trends in Computing.
[18] Hossain, M.E. and Chetty, G., 2011, Human identity verification by using physiological and behavioural biometric traits, Int. J. Biosci. Biochem. Bioinform. 1: 199-205.
[19] Waluś, M., Bernacki, K. and Konopacki, J., 2017, Impact of NIR wavelength lighting in image acquisition on finger vein biometric system effectiveness, Opto-Electron. Rev. 25: 263-268.