Recognition of Passports using Enhanced Neural Networks and Photo Authentication

개선된 신경망과 사진 인증을 이용한 여권 인식

  • 김광백 (신라대학교 컴퓨터공학과) ;
  • 박현정 (신라대학교 건축학부)
  • Published : 2006.05.01

Abstract

Current emigration and immigration control inspects passports by the naked eye, registers them by manual input, and compares them with items of database. In this paper, we propose the method to recognize information codes of passports. The proposed passport recognition method extracts character-rows of information codes by applying sobel operator, horizontal smearing, and contour tracking algorithm. The extracted letter-row regions is binarized. After a CDM mask is applied to them in order to recover the individual codes, the individual codes are extracted by applying vertical smearing. The recognizing of individual codes is performed by the RBF network whose hidden layer is applied by ART 2 algorithm and whose learning between the hidden layer and the output layer is applied by a generalized delta learning method. After a photo region is extracted from the reference of the starting point of the extracted character-rows of information codes, that region is verified by the information of luminance, edge, and hue. The verified photo region is certified by the classified features by the ART 2 algorithm. The comparing experiment with real passport images confirmed the good performance of the proposed method.

References

  1. 전달수, '체류 외국인 동향조사 종합보고II (출입국심사제도 개선),' 법무부체류심사과, 2001
  2. Kim, K. B., Cho, J. H., Kim, C. K., 'Recognition of Passports Using FCM-Based RBF Network,' Lecture Notes in Artificial Intelligence, LNAI 3809, Springer, pp.1241-1245, 2005
  3. Waranbe, M., K. Kuwata and Katayma, R., 'Adaptive Tree-Structured Self Generating Radial Basis Function and its Application to Nonlinear Identification Problem,' Proceedings of IIZUKA, pp.167 -170, 1994
  4. Kothari, M. L., Madnani, S., and Segal, R., 'Orthogonal Least Square Learning Algorithm Based Radial Basis Function Network Adaptive Power System Stabilizer,' Proceedings of IEEE SMC, Vol. 1, pp.542-547, 1997
  5. Kim, K. B., Kang, M. H., and Cha, E. Y., 'A Fuzzy Self_Organized Backpropagation using Nervous System,' Proceedings. IEEE SMC, Vol.5, pp.1457-1462, 1997
  6. Jain, A. K. Fundamental of Digital Image Processing, Englewood Cliffs, New Jersey: Prentice-Hall, 1989