International Journal of Fuzzy Logic and Intelligent Systems

  • 제3권1호
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  • Pages.27-31
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  • 2003
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  • 1598-2645(pISSN)
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  • 2093-744X(eISSN)
한국지능시스템학회 (Korean Institute of Intelligent Systems)
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A Robust On-line Signature Verification System

  • Ryu, Sang-Yeun (Chungbuk National University, School of Electrical and Computer Engineering) ;
  • Lee, Dae-Jong (Electrical Safety Research Institute) ;
  • Chun, Myung-Geun (Chungbuk National University, School of Electrical and Computer Engineering)
  • 발행 : 2003.06.01
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초록

This paper proposes a robust on-line signature verification system based on a new segmentation method and fusion scheme. The proposed segmentation method resolves the problem of segment-to-segment comparison where the variation between reference signature and input signature causes the errors in the location and the number of segments. In addition, the fusion scheme is adopted, which discriminates genuineness by calculating each feature vector's fuzzy membership degree yielded from the proposed segmentation method. Experimental results show that the proposed signature verification system has lower False Reject Rate(FRR) for genuine signature and False Accept Rate(FAR) for forgery signature.

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참고문헌

  1. Myung-Geun Chun, Introductin to Biometrics, ICU, PP.8-1-21, 2002
  2. Chin-Chuan Han, 'An on-line signature verificationsystem using multi-template matching approaches',Security Technology, Proceedings. IEEE 33rd AnnualInternational Camahan Conference on , PP. 477-480,1999
  3. Ma Mingming, 'Automatic on-line signature verificationbased on multiple models', Computational Intelligence for Financial Engineering, (CIFEr) Proceedings of theIEEE/IAFE/INF0RMS Conference on , PP. 30 -33, 2000
  4. Rhee T.H., 'On-line signature verification usingmodel-guided segmentation and discriminative featureselection for skilled forgeries', Document Analysis and Recognition, Proceedings. Sixth International Conference on , PP. 645 -649, 2001
  5. Yue K..W., 'Improved segmentation and segmentassociation for on-line signature verification', Systems,Man, and Cybernetics, IEEE International Conference on, Vol. 4 , 2000
  6. Brault, J.-J., Plamondon R., 'Segmenting handwrittensignatures at their perceptually important points', Pattem Analysis and Machine Intelligence, IEEE Transactions on, Volume: 15 Issue: 9 , Sep 1993
  7. Schmidt C., Kraiss K.-F., 'Establishment of personalizedtemplates for automatic signature verification', Document Analysis and Recognition, Proceedings of the FourthInternational Conference on , Vol. 1, PP. 263-267, 1997
  8. Kiran G.V., Kunte R.S.R., Samuel S., 'On-line signatureverification system using probabilistic feature modelling', Signal Processing and its Applications, Sixth International, Symposium on., Vol. 1, PP. 355 -358,2001 https://doi.org/10.1109/ISSPA.2001.949851
  9. Fuentes, M., Garcia-Salicetti, S., Dorizzi B., 'On linesignature verification: fusion of a hidden markov modeland a neural network via a support vector machine',frontiers in Handwriting Recognition, Proceedings. EighthInternational Workshop on , PP. 253-258, 2002
  10. Wan-Suck Lee, Mohankrishnan N., Paulik M.J- 'Improved segmentation through dynamic time warping for signature verification using a neural network classifier', Image Processing, ICIP 98. Proceedings. International Conference on, Vol. 2, PP. 929-933, 1998 https://doi.org/10.1109/ICIP.1998.723707
  11. Ma Mingming, Wijesoma W.S., Sung E., 'An automatic on-line signature verification system based on three models', Electrical and Computer Engineering, 2000 Canadian Conference on , Vol. 2 , PP. 890-894, 2000
  12. Fuentes M, Garcia-Salicetti S., Dorizzi B., 'Onlinsignature verification; fusion of a hidden markov modeland a neural network via a support vector machin', Frontiers in Handwriting Recognition, Proceedings.Eighth International Workshop on, PP. 253-258, 2002

피인용 문헌

  1. Forged Signature Distinction Using Convolutional Neural Network for Feature Extraction vol.8, pp.2, 2018, https://doi.org/10.3390/app8020153