Off-line signature verification with PSO-NN algorithm

Analysis of signature is a widely used and developed area of research for personal verification. A typical signature verification system generally consists of four components: data acquisition, pre-processing, feature extraction and verification. This paper presents a novel technique for off-line signature verification (SV). The technique is based on a neural network (NN) approach trained with particle swarm optimization (PSO) algorithm. To test the performance of the proposed PSO-NN algorithm three types of forgeries; random, unskilled and skilled are examined and the experimental results are illustrated.

[1]  I. Pottier,et al.  Identification and authentification of handwritten signatures with a connectionist approach , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[2]  Ng Geok See,et al.  A neural network approach for off-line signature verification , 1993, Proceedings of TENCON '93. IEEE Region 10 International Conference on Computers, Communications and Automation.

[3]  Sukhan Lee,et al.  Offline tracing and representation of signatures , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[4]  Sargur N. Srihari,et al.  Offline Signature Verification And Identification Using Distance Statistics , 2004, Int. J. Pattern Recognit. Artif. Intell..

[5]  Robert Sabourin,et al.  Evaluation of a training method and of various rejection criteria for a neural network classifier used for off-line signature verification , 1994, Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94).

[6]  Madasu Hanmandlu,et al.  Off-line signature verification and forgery detection using fuzzy modeling , 2005, Pattern Recognit..

[7]  Miguel Angel Ferrer-Ballester,et al.  Offline geometric parameters for automatic signature verification using fixed-point arithmetic , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Yuan Yan Tang,et al.  Off-line signature verification by the tracking of feature and stroke positions , 2003, Pattern Recognit..

[9]  Rong-Chun Zhao,et al.  Off-line signature verification incorporating the prior model , 2003, Proceedings of the 2003 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.03EX693).

[10]  Flávio Bortolozzi,et al.  An off-line signature verification method based on the questioned document expert's approach and a neural network classifier , 2004, Ninth International Workshop on Frontiers in Handwriting Recognition.

[11]  Yingyong Qi,et al.  Signature verification using global and grid features , 1994, Pattern Recognit..

[12]  Koldo Espinosa,et al.  Applying dynamic methods in off-line signature recognition , 2004, SPIE Defense + Commercial Sensing.

[13]  Robert Sabourin,et al.  Off-line signature verification using fuzzy ARTMAP neural network , 1995, Proceedings of ICNN'95 - International Conference on Neural Networks.

[14]  Sargur N. Srihari,et al.  Biometric and Forensic Aspects of Digital Document Processing , 2007 .

[15]  Karim Faez,et al.  Signature verification using shape descriptors and multiple neural networks , 1997, TENCON '97 Brisbane - Australia. Proceedings of IEEE TENCON '97. IEEE Region 10 Annual Conference. Speech and Image Technologies for Computing and Telecommunications (Cat. No.97CH36162).

[16]  Ben M. Herbst,et al.  Offline Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model , 2004, EURASIP J. Adv. Signal Process..

[17]  Georgy Kukharev,et al.  IMAGE ANALYSIS AND PATTERN RECOGNITION IN BIOMETRIC TECHNOLOGIES , 2001 .

[18]  Ge Xiurun,et al.  An improved PSO-based ANN with simulated annealing technique , 2005, Neurocomputing.

[19]  Vinayak Balkrishana Kulkarni.  A Colour Code Algorithm For Signature Recognition , 2007 .

[20]  Gerry Dozier,et al.  Adapting Particle Swarm Optimizationto Dynamic Environments , 2001 .

[21]  Peng-Yeng Yin,et al.  Particle swarm optimization for point pattern matching , 2006, J. Vis. Commun. Image Represent..

[22]  Kejun Wang,et al.  A survey of off-line signature verification , 2004 .

[23]  M. Yusof,et al.  Signature verification and forgery detection system , 2003, Proceedings. Student Conference on Research and Development, 2003. SCORED 2003..

[24]  Hong Yan,et al.  Off-line signature verification based on geometric feature extraction and neural network classification , 1997, Pattern Recognit..

[25]  Peng-Yeng Yin,et al.  A discrete particle swarm algorithm for optimal polygonal approximation of digital curves , 2004, J. Vis. Commun. Image Represent..

[27]  Masato Nakajima,et al.  An active search method for local individual features in off-line signature verification , 2003, Systems and Computers in Japan.

[28]  Réjean Plamondon,et al.  A complexity measure of handwritten curves: modeling of dynamic signature forgery , 1993, IEEE Trans. Syst. Man Cybern..

[29]  Bijan Shirinzadeh,et al.  Prediction of geometric errors of robot manipulators with Particle Swarm Optimisation method , 2006, Robotics Auton. Syst..

[30]  Jean-Baptiste Fasquel,et al.  A hybrid opto-electronic method for fast off-line handwritten signature verification , 2004, Document Analysis and Recognition.

[31]  Michael R. Lyu,et al.  A hybrid particle swarm optimization-back-propagation algorithm for feedforward neural network training , 2007, Appl. Math. Comput..

[32]  Ruowei Zhou,et al.  An automatic fuzzy neural network driven signature verification system , 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

[33]  N. K. Bose,et al.  Neural Network Fundamentals with Graphs, Algorithms and Applications , 1995 .

[34]  Robert Sabourin,et al.  Off-line signature verification using directional PDF and neural networks , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol.II. Conference B: Pattern Recognition Methodology and Systems.

[35]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[36]  H. Baltzakisa,et al.  A new signature verification technique based on a two-stage neural network classifier , 2000 .

[37]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[38]  Sukhan Lee,et al.  Offline tracing and representation of signatures , 1992, IEEE Trans. Syst. Man Cybern..

[39]  Hong-Bo Liu,et al.  Neural networks learning using vbest model particle swarm optimisation , 2004, Proceedings of 2004 International Conference on Machine Learning and Cybernetics (IEEE Cat. No.04EX826).

[40]  Yu Li,et al.  Particle swarm optimisation for evolving artificial neural network , 2000, Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0.