School Debit Transaction Using Fingerprint Recognition System

Authors

  • Wai Kit Wong Multimedia University
  • Thu Soe Min Multimedia University
  • Shi Enn Chong Multimedia University

DOI:

https://doi.org/10.30564/aia.v1i2.1202

Abstract

This paper proposed a fingerprint based school debit transaction system using minutiae matching biometric technology. This biometric cashless transaction system intensely shortens the luncheon line traffic and labour force compared to conventional cash payment system. Furthermore, contrast with card cashless transaction system, fingerprint cashless transaction system with benefit that user need not carry additional identification object and remember lengthy password. The implementation of this cashless transaction system provides a more organize, reliable and efficient way to operate the school debit transaction system. 

Keywords:

Fingerprint recognition; Biometric authentication; Image processing

References

[1] D. Thaktar. Biometric Solution for Schools- Fingerprint lunch line. Bayometric, 2018. From: https://www.bayometric.com/biometric-solution-schools-fingerprint-lunch-line/

[2] J. Trader. Why School Districts Should Implement Cashless Fingerprint Payment System, M2SYS Technology, 2016. From: http://www.m2sys.com/blog/education/why-school-districts-should-implement-cashless-fingerprint-payment-system/

[3] C. Kalyani. Various Biometric Authentication Technique: A Review. Journal of Biometrics & Biostatistics, 2017, 08(05).

[4] S. Hashemi, H. Tann, F. Buttafuoco and S. Reda. Approximate Computing for Biometric Security Systems: A Case Study on Iris Scanning. 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE), 2018: 319-324.

[5] N. Charfi. Biometric recognition based on hand schape and palmprint modalities. Image Processing [eess.IV]. Ecole nationale supérieure Mines-Télécom Atlantique, 2017.

[6] M. M. H. Ali, V. H. Mahale, P. Yannawar and A. T. Gaikwad. Overview of fingerprint recognition system. 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT), Chennai, 2016: 1334-1338.

[7] R. Mansoor & B. Parisa. A Review Of Face Recognition Methods. International Journal of Pattern Recognition and Artificial Intelligence, 2013, 27(4): 1356005(1 -35).

[8] M. K. Sharma & O. Kumar. Speech Recognition: A Review. Special Conference Issue: National Conference on Cloud Computing & Big Data, 2014: 62-71.

[9] J. Choudhary. Survey of Different Biometric Techniques. International Journal of Modern Engineering Research (IJMER), 2012.

[10] M. N. Anjana Doshi. Biometric Recognition Techniques. International Journal of Advanced Research in Computer Networking, Wireless and Mobile Communications, 2015, 2(1): 143-152.

[11] D. Thaktar. False Acceptance Rate (FAR) and False Recognition Rate (FRR). Bayometric, 2017. From:https://www.bayometric.com/false-acceptance-rate-far-false-recognition-rate-frr/

[12] W. Yang, S. Wang, J. Hu, G. Zheng and C. Valli. Security and Accuracy of Fingerprint-Based Biometrics: A Review. Symmetry, 2019, 11(141): 1-19.

[13] "Intergalactic Vault," [Online]. Available:http://www.intergalacticvault.com/if-you-have-a-spiral-whorl-fingerprint-pattern-this-iswhat-it-means/

[14] J. Qi, Z. Shi, X. Zhao and Y. Wang. A Novel Fingerprint Matching Method Based On The Hough Transform Without Quantization Of The Hough Space. Proceeding of the Third International Conference on Image and Graphics (ICIG’ 04) Hong Kong, China, 2004: 262-265.

[15] N. Saroha and N. S. Gill. Hough Transform Based Fingerprint Matching Using Minutiae Extraction. International Journal of Advanced Research in Computer Science, 2013, 4(10): 117-120.

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How to Cite

Wong, W. K., Min, T. S., & Chong, S. E. (2019). School Debit Transaction Using Fingerprint Recognition System. Artificial Intelligence Advances, 1(2), 24–37. https://doi.org/10.30564/aia.v1i2.1202

Issue

Vol. 1 , Iss. 2 (October 2019)

Article Type

Article

License

Copyright © 2019 Author(s)

Creative Commons License

This is an open access article under the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) License.

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