Online Signature Verification Using Fourier Descriptors

被引:0
|
作者
Berrin Yanikoglu
Alisher Kholmatov
机构
[1] Sabanci University,Faculty of Engineering and Natural Sciences
[2] Scientific and Technological Research Council of Turkey (TUBITAK),National Research Institute of Electronics and Cryptology (UEKAE)
关键词
Fast Fourier Transform; Dynamic Time Warping; Fourier Domain; Normalization Step; Public Signature;
D O I
暂无
中图分类号
学科分类号
摘要
We present a novel online signature verification system based on the Fast Fourier Transform. The advantage of using the Fourier domain is the ability to compactly represent an online signature using a fixed number of coefficients. The fixed-length representation leads to fast matching algorithms and is essential in certain applications. The challenge on the other hand is to find the right preprocessing steps and matching algorithm for this representation. We report on the effectiveness of the proposed method, along with the effects of individual preprocessing and normalization steps, based on comprehensive tests over two public signature databases. We also propose to use the pen-up duration information in identifying forgeries. The best results obtained on the SUSIG-Visual subcorpus and the MCYT-100 database are 6.2% and 12.1% error rate on skilled forgeries, respectively. The fusion of the proposed system with our state-of-the-art Dynamic Time Warping (DTW) system lowers the error rate of the DTW system by up to about 25%. While the current error rates are higher than state-of-the-art results for these databases, as an approach using global features, the system possesses many advantages. Considering also the suggested improvements, the FFT system shows promise both as a stand-alone system and especially in combination with approaches that are based on local features.
引用
收藏
相关论文
共 50 条
  • [21] Identity authentication using improved online signature verification method
    Kholmatov, A
    Yanikoglu, B
    PATTERN RECOGNITION LETTERS, 2005, 26 (15) : 2400 - 2408
  • [22] Automatic Online Signature Verification: A Prototype Using Neural Networks
    Ahmed, Syed Khaleel
    Ramasamy, Agileswari K.
    Khairuddin, Anis Salwa Mohd.
    Omar, Jamaludin
    TENCON 2009 - 2009 IEEE REGION 10 CONFERENCE, VOLS 1-4, 2009, : 1448 - 1451
  • [23] Online Signature Verification Using Bidirectional Recurrent Neural Network
    Nathwani, Chirag
    PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND CONTROL SYSTEMS (ICICCS 2020), 2020, : 1076 - 1078
  • [24] Statistical on-line signature verification using rotation-invariant dynamic descriptors
    Nilchiyan, M. R.
    Yusof, R. Bte
    Alavi, S. E.
    2015 10TH ASIAN CONTROL CONFERENCE (ASCC), 2015,
  • [25] Online hand signature verification: A review
    Sayeed S.
    Samraj A.
    Besar R.
    Hossen J.
    Journal of Applied Sciences, 2010, 10 (15) : 1632 - 1643
  • [26] Online Signature Verification for Forgery Detection
    Rizwan, Muhammad
    Aadil, Farhan
    Durrani, Mehr Yahya
    Thinakaran, Rajermani
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2023, 14 (03) : 478 - 484
  • [27] Online signature verification by spectrogram analysis
    Alpar, Orcan
    Krejcar, Ondrej
    APPLIED INTELLIGENCE, 2018, 48 (05) : 1189 - 1199
  • [28] An Intelligent System for Online Signature Verification
    Sarfraz, Muhammad
    Rizvi, Syed M. A. J.
    2015 SECOND INTERNATIONAL CONFERENCE ON INFORMATION SECURITY AND CYBER FORENSICS (INFOSEC), 2015, : 17 - 22
  • [29] Online signature verification by spectrogram analysis
    Orcan Alpar
    Ondrej Krejcar
    Applied Intelligence, 2018, 48 : 1189 - 1199
  • [30] Uniform Segmentation in Online Signature Verification
    Ansari, Abdul Quaiyum
    Kour, Jaspreet
    2015 ANNUAL IEEE INDIA CONFERENCE (INDICON), 2015,