Comparative Analysis of Offline Signature Verification System

被引:0
|
作者
Yadav, Deepti [1 ]
Tyagi, Ranbeer [2 ]
机构
[1] MPCT Coll, EC, Gwalior, India
[2] MPCT Coll, Dept EC, Gwalior, India
关键词
Digital signature; biometric techniques; offline signature; feature extraction; Applications;
D O I
10.14257/ijsia.2015.9.9.13
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A digital signature is a mathematical structure for indicating the validity of digital information or any document. A message is created by a known sender whose digital signature provides a recipient reason, such that the sender cannot reject having sent the message confirmation and that the message was not changed in transportation integrity. The Signature recognition and verification are a behavioral biometric. It can be operated in two various types: one is the Off-Line or Static Signature Verification Technique and another is the On-line or Dynamic Signature Verification Technique. In this paper, we are studying about Off-Line or Static Signature Verification Technique. In this method, users write their own signature on the blank paper and then digitize it with an optical scanner or a camera, and then the biometric system identifies the signature by analyzing its shape and this collection is also called as "off-line" Signature verification. Signature authentication can be divided into three main classes. These classes are based on how alike a forgery is in relation to signature and are identified as random, simple and skilled. In the random forgery the forger does not know about the signer's shape or signature name. In the simple forgery or unskillful forgery, the forger knows the name of the actual signer but don't know how his signature looks like. And in the skilled forgery, the forger knows both the information of the signer.
引用
收藏
页码:141 / 150
页数:10
相关论文
共 50 条
  • [1] Comparative analysis of offline signature verification system
    Yadav, Deepti
    Tyagi, Ranbeer
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (11) : 355 - 364
  • [2] A Comparative Study of Various Methods for Offline Signature Verification
    Jain, Urmila A.
    Patil, Nitin N.
    PROCEEDINGS OF THE 2014 INTERNATIONAL CONFERENCE ON ISSUES AND CHALLENGES IN INTELLIGENT COMPUTING TECHNIQUES (ICICT), 2014, : 760 - 764
  • [3] A new system for offline signature identification and verification
    Ghandali, Samaneh
    Moghaddam, Mohsen Ebrahimi
    Khosravi, Mohammad Javad
    INTERNATIONAL JOURNAL OF SIGNAL AND IMAGING SYSTEMS ENGINEERING, 2012, 5 (02) : 123 - 131
  • [4] Offline signature verification by the analysis of cursive strokes
    Fang, BN
    Wang, YY
    Leung, CH
    Tse, KW
    Tang, YY
    Kwok, PCK
    Wong, YK
    INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE, 2001, 15 (04) : 659 - 673
  • [5] Writer-Independent Offline Signature Verification System
    Jayaraman, Malini
    Gadwala, Surendra Babu
    DATA MANAGEMENT, ANALYTICS AND INNOVATION, ICDMAI 2018, VOL 2, 2019, 839 : 213 - 223
  • [6] Optimized Classification Approach For Offline Signature Verification System
    Thakare, Bhushan S.
    Deshmukh, Hemant R.
    2018 3RD INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2018,
  • [7] Offline Chinese signature verification system with information fusion
    Ding, YY
    Chen, QH
    Wang, JS
    THIRD INTERNATIONAL SYMPOSIUM ON MULTISPECTRAL IMAGE PROCESSING AND PATTERN RECOGNITION, PTS 1 AND 2, 2003, 5286 : 875 - 878
  • [8] Offline signature verification system based on the online data
    Zimmer, Alessandro
    Ling, Lee Luan
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2008, 2008
  • [9] FREEMAN CHAIN CODE AS REPRESENTATION IN OFFLINE SIGNATURE VERIFICATION SYSTEM
    Azmi, Aini Najwa
    Nasien, Dewi
    Abu Samah, Azurah
    JURNAL TEKNOLOGI-SCIENCES & ENGINEERING, 2016, 78 (8-2): : 89 - 94
  • [10] Offline Handwritten Signature Modeling and Verification Based on Archetypal Analysis
    Zois, Elias N.
    Theodorakopoulos, Ilias
    Economou, George
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, : 5515 - 5524