Online Signature Verification with Neural Networks Classifier and Fuzzy Inference

被引:5
|
作者
Khalid, Marzuki [1 ]
Mokayed, Hamam [1 ]
Yusof, Rubiyah [1 ]
Ono, Osamu [2 ]
机构
[1] Univ Teknol Malaysia, CAIRO, Jalan Semarak, Kuala Lumpur 54100, Malaysia
[2] Meiji Univ, Inst Appl DNA Comp, Kanagawa 2148571, Japan
来源
2009 THIRD ASIA INTERNATIONAL CONFERENCE ON MODELLING & SIMULATION, VOLS 1 AND 2 | 2009年
关键词
RECOGNITION;
D O I
10.1109/AMS.2009.23
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Compared to physiologically based biometric systems such as fingerprint, face, palm-vein and retina, behavioral based biometric systems such as signature, voice, gait, etc. are less popular and many are still in their infancy. A major problem is due to inconsistencies in human behavior which require more robust algorithms in their developments. In this paper, an online signature verification system is proposed based on neural networks classifier and fuzzy inference. The software has been developed with a robust validation module based on Pearson's cot-relation algorithm in which more consistent sets Of user's signature are enrolled. In this way, more consistent sets of training patterns are used to train the neural network modules based on the popular back-propagation algorithm. To increase the robustness not only the neural network threshold is used for the verification, the time and length of the signature are also calculated. A fuzzy inference module is then set lip to infer the three thresholds for human-like decision outputs. The signature verification system shows better consistency and is more robust than previous designs.
引用
收藏
页码:236 / +
页数:2
相关论文
共 50 条
  • [31] Signature verification using shape descriptors and multiple neural networks
    Dehghan, M
    Faez, K
    Fathi, M
    IEEE TENCON'97 - IEEE REGIONAL 10 ANNUAL CONFERENCE, PROCEEDINGS, VOLS 1 AND 2: SPEECH AND IMAGE TECHNOLOGIES FOR COMPUTING AND TELECOMMUNICATIONS, 1997, : 415 - 418
  • [32] A new signature verification technique based on a two-stage neural network classifier
    Baltzakis, H
    Papamarkos, N
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2001, 14 (01) : 95 - 103
  • [33] Genetically optimized hybrid Fuzzy Neural Networks with the aid of TSK fuzzy inference rules and Polynomial Neural Networks
    Oh, SK
    Pedryez, W
    Kim, HK
    Kim, YK
    COMPUTATIONAL INTELLIGENCE AND BIOINSPIRED SYSTEMS, PROCEEDINGS, 2005, 3512 : 407 - 415
  • [34] Online Signature Verification System
    Julita, A.
    Fauziyah, S.
    Azlina, O.
    Mardiana, B.
    Hazura, H.
    Zahariah, A. M.
    CSPA: 2009 5TH INTERNATIONAL COLLOQUIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, 2009, : 8 - 12
  • [35] Signature barcodes for online verification
    Alpar, Orcan
    PATTERN RECOGNITION, 2022, 124
  • [36] A Dempster-Shafer theory based classifier combination for online Signature recognition and verification systems
    Ghosh, Rajib
    Kumar, Pradeep
    Roy, Partha Pratim
    INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS, 2019, 10 (09) : 2467 - 2482
  • [37] Speaker Verification Based on Fuzzy Classifier
    Dustor, Adam
    MAN-MACHINE INTERACTIONS, 2009, 59 : 389 - 397
  • [38] Application of fuzzy inference algorithm in artificial neural networks forecasting
    Yang, KH
    Wang, BS
    Zhao, LL
    Xu, H
    PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 1, 2004, : 445 - 450
  • [39] A Dynamic Time Warping and Deep Neural Network Ensemble for Online Signature Verification
    Gwetu, Mandlenkosi Victor
    MACHINE LEARNING FOR NETWORKING, MLN 2020, 2021, 12629 : 141 - 153
  • [40] A study on neural networks and fuzzy inference systems for transient data
    Temurtas, F
    ARTIFICIAL INTELLIGENCE: METHODOLOGY, SYSTEMS, AND APPLICATIONS, PROCEEDINGS, 2004, 3192 : 277 - 284