Online Signature Verification using Hybrid Features

被引：0
|
作者：
Tahir, Madiha [1 ]
Akram, M. Usman [1 ]
机构：
[1] Natl Univ Sci & Technol, Comp Engn, Rawalpindi, Pakistan
来源：
2015 SECOND INTERNATIONAL CONFERENCE ON INFORMATION SECURITY AND CYBER FORENSICS (INFOSEC) | 2015年
关键词：
biometric system; hybrid features; online signature verification; skilled forgeries;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Biometrics is the process by which a person's physical, behavioral and psychological traits are identified and recorded by an electronic device of identity. Online handwritten signature verification is a biometric based security system. Most of the previous work is based on statistics of online signatures, local and global features. We proposed to test hybrid features on Japanese online dataset from ICDAR2013 [38]. We extract features in frequency domain and time domain as well by using combination of global, Fourier transform and wavelet transform based features. Accuracy is calculated to compare the efficiency of proposed method. It shows that combination of global, DWT and FFT based features yields better results than other combinations. The accuracy achieved by our system is 73.49% which is better than previous systems evaluated on Japanese online dataset.
引用
收藏
页码：11 / 16
页数：6
相关论文
共 50 条
  • [1] Online Signature Verification using Hybrid Transform Features
    Mlaba, Andile
    Gwetu, Mandlenkosi
    Viriri, Serestina
    [J]. 2018 CONFERENCE ON INFORMATION COMMUNICATIONS TECHNOLOGY AND SOCIETY (ICTAS), 2018,
  • [2] Online Signature Verification using Segmented Local Features
    Tahir, Madiha
    Akram, M. Usman
    Idris, Muhammad Arslan
    [J]. 2016 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRONIC AND ELECTRICAL ENGINEERING (ICE CUBE), 2016, : 100 - 105
  • [3] Signature verification approach using fusion of hybrid texture features
    Bhunia, Ankan Kumar
    Alaei, Alireza
    Roy, Partha Pratim
    [J]. NEURAL COMPUTING & APPLICATIONS, 2019, 31 (12): : 8737 - 8748
  • [4] Signature verification approach using fusion of hybrid texture features
    Ankan Kumar Bhunia
    Alireza Alaei
    Partha Pratim Roy
    [J]. Neural Computing and Applications, 2019, 31 : 8737 - 8748
  • [5] Online Signature Verification Based on Biometric Features
    Li, Nan
    Liu, Jiafen
    Li, Qing
    Luo, Xubin
    Duan, Jiang
    [J]. PROCEEDINGS OF THE 49TH ANNUAL HAWAII INTERNATIONAL CONFERENCE ON SYSTEM SCIENCES (HICSS 2016), 2016, : 5527 - 5534
  • [6] Online Signature Verification Using Neural Network and Pearson Correlation Features
    Iranmanesh, Vahab
    Ahmad, Sharifah Mumtazah Syed
    Adnan, Wan Azizun Wan
    Malallah, Fahad Layth
    Yussof, Salman
    [J]. 2013 IEEE CONFERENCE ON OPEN SYSTEMS (ICOS), 2013, : 18 - +
  • [7] Optimal prototype functions of features for online signature verification
    Romo, JCM
    Silva, RA
    [J]. INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2004, 18 (07) : 1189 - 1206
  • [8] Online signature verification based on segment features and hmm
    Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031, China
    不详
    [J]. Moshi Shibie yu Rengong Zhineng, 2007, 1 (95-100):
  • [9] The Usability of Derived Function Features in Online Signature Verification
    Szucs, Cintia Lia
    Kovari, Bence
    [J]. 2022 9TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING & MACHINE INTELLIGENCE, ISCMI, 2022, : 192 - 197
  • [10] Online Signature Verification using Hybrid Wavelet Transform with Hidden Markov Model
    Chavan, Manoj
    Singh, Ravish R.
    Bharadi, Vinayak A.
    [J]. 2017 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, CONTROL AND AUTOMATION (ICCUBEA), 2017,
12345