Earticle

초록

영어

Recently bank card number recognition plays an important role in improving payment efficiency. In this paper we propose a new bank-card number identification algorithm. The proposed algorithm consists of three modules which include edge detection, candidate region generation, and recognition. The module of ‘edge detection’ is used to obtain the possible digital region. The module of ‘candidate region generation’ has the role to expand the length of the digital region to obtain the candidate card number regions, i.e. to obtain the final bank card number location. And the module of ‘recognition’ has Convolutional deep learning Neural Network (CNN) to identify the final bank card numbers. Experimental results show that the identification rate of the proposed algorithm is 95% for the card numbers, which shows 20% better than that of conventional algorithm or method.

목차

Abstract
1. Introduction
2. Proposed Algorithm
2.1 Edge Detection
2.2 Candidate Region Generation
2.3 Recognition
3. Simulation Results
3.1 Candidate card number region generation
3.2 Identification rate as a performance
4. Conclusion
Acknowledgement
References

키워드

저자

• Rui-Xia Shi [ Ph.D, Graduate, Dept. of Energy and Electrical Eng., Woosuk Univeristy, Korea ]
• Dong-Gyu Jeong [ Professor, Faculty of Computer Eng., Woosuk Univeristy, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380