A Review on Various Credit Card Transaction Based on Face Recognition

Authors

  • Payal Sahare  BE Student, Computer Technology, K. D. K. College of Engineering, Nagpur, Maharashtra, India
  • Rohini Khobragade  BE Student, Computer Technology, K. D. K. College of Engineering, Nagpur, Maharashtra, India
  • Sachi Ambade  BE Student, Computer Technology, K. D. K. College of Engineering, Nagpur, Maharashtra, India
  • Samiksha Deshmukh  BE Student, Computer Technology, K. D. K. College of Engineering, Nagpur, Maharashtra, India
  • Prof. S. M. Malode  Assistant Professor, Computer Technology, K. D. K. College of Engineering, Nagpur, Maharashtra, India

Keywords:

Credit Card Fraud, Transaction, Verification, Face Recognize, Image Processing

Abstract

Money is an important thing in this world. The payment modes at Point of Sales (PoS) have different modes such as cash on delivery, online transaction, credit card transaction and monthly instalments etc. Whenever online transactions take place, the customer involves opting for credit/debit cards or internet banking. The credit card provides prominent use of payment method, so it is followed in many scenarios. As we know, during online transactions there are many chances to steal the confidential information by the attackers or hackers. The recent progress in biometric identification techniques, including finger printing, retina scanning, and facial recognition has made a great efforts to rescue the unsafe situation at the Credit Card Transactions. In this paper, we looked into the various system that integrates facial recognition technology for identity verification process for Credit Card Transactions.

References

  1. Anshul Singh, Devesh Narayan. (2012), ‘A Survey on Hidden Markov Model for Credit Card Fraud Detection’, (IJEAT) ISSN: 2249 – 8958, Volume-1, Issue-Ant´onio Miguel Louren¸co. (2009), “Techniques for keypoint detection and matching between endoscopic images”.
  2. Avinash Ingole, Dr. R. C. Thool. (2013), “Credit Card Fraud Detection Using Hidden Markov Model and Its Performance”, ijarcsse, Volume 3, Issue 6, pp. 626-632
  3. Clifton phua, Vincent Lee, Kate Smith & Ross Gayler. (2010), “A Comprehensive Survey of Data Mining-based Fraud Detection Research”
  4. D. Madhu Babu, M. Bhagyasri, K. Lahari, CH. Madhuri, G. Pushpa Kumari. (2014), “Image Based Fraud Prevention”, (IJCSIT), Vol. 5 (1), pp.728-731
  5. Dipti Deodhare, NNR Ranga Suri R. Amit. (2005), “Preprocessing and Image Enhancement Algorithms for a Form-based Intelligent Character Recognition System”, IJCSA, Vol. II, No. II, pp.131 - 144
  6. Dong ping, Tian. (2013), “A Review on Image Feature Extraction and Representation Techniques”, IJMUE, Vol. 8, No. 4, pp.385-395
  7. https://www.jumio.com/2011/07/jumio-turns-webcam-into-credit-card-reader/
  8. http://www.marketcalls.in/credit-cards/the-history-of-credit-cards.html
  9. http://wwwen.uni.lu/snt/research/research_projects2/prevention_of_fraud_by_pattern_detection_in_credit_card_transaction
  10. Khyati Chaudhary, Jyoti Yadav Bhawna Mallick. (2012), “A review of Fraud Detection Techniques: Credit Card”, IJCA, Vol. 45, No. 1, pp.39-44
  11. Kumar.G. (2014), “A Detailed Review of Feature Extraction in Image Processing Systems”, ACCT, pp.5 - 12
  12. Mark S. Nixon, Alberto S. Aguado. (2008), “Feature Extraction and Image Processing”, ISBN 0 7506 5078 8
  13. Rashmi G.Dukhi. (2011), “Soft Computing Tools in Credit card fraud & Detection”, ijetae.com, ISSN 2250-2459, Volume 1, Issue 2, pp. 60-64
  14. Vinay Hiremath, Ashwini Mayakar. (2012), “FACE RECOGNITION USING EIGENFACE APPROACH”

Downloads

Published

2019-09-30

Issue

Section

Research Articles

How to Cite

[1]
Payal Sahare, Rohini Khobragade, Sachi Ambade, Samiksha Deshmukh, Prof. S. M. Malode, " A Review on Various Credit Card Transaction Based on Face Recognition, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 5, pp.24-28, September-October-2019.