An efficient offline signature identification method based on Fourier Descriptor and chain codes

This paper proposes a novel offline signature identification method based on Fourier Descriptor (FD) and Chain Codes features. Signature identification was classified into two different problems: recognition and verification. In recognition process, we used Principle Component Analysis. In verification process, we designed a multilayer feed forward artificial neural network. The main steps of constructing a signature identification system are discussed and experiments on real data sets show that the average error rate can reach 3.8%.

[1]  Sebastiano Impedovo,et al.  A Multi-expert System for Dynamic Signature Verification , 2000, Multiple Classifier Systems.

[2]  Yuan Yan Tang,et al.  Model-based signature verification with rotation invariant features , 2009, Pattern Recognit..

[3]  Nikolaos Papanikolopoulos,et al.  Signature identification through the use of deformable structures , 1998, Signal Process..

[4]  Philip N. Klein,et al.  On Aligning Curves , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Flávio Bortolozzi,et al.  Off-line signature verification using HMM for random, simple and skilled forgeries , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[6]  Suh-Yin Lee,et al.  On-line signature verification based on split-and-merge matching mechanism , 1997, Pattern Recognit. Lett..

[7]  Lawrence Sirovich,et al.  Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Alfred Mertins,et al.  Line segment distribution of sketches for Persian signature recognition , 2003, TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region.

[9]  Chong Wang,et al.  Off-line Chinese signature verification based on support vector machines , 2005, Pattern Recognit. Lett..

[10]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[11]  Hong Yan,et al.  Handwritten signature verification based on neural 'gas' based vector quantization , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[12]  Inan Güler,et al.  A different approach to off-line handwritten signature verification using the optimal dynamic time warping algorithm , 2008, Digit. Signal Process..

[13]  Gerhard Rigoll,et al.  A systematic comparison between on-line and off-line methods for signature verification with hidden Markov models , 1998, Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170).

[14]  W. Turin,et al.  On-line handwritten signature verification using hidden Markov model features , 1997, Proceedings of the Fourth International Conference on Document Analysis and Recognition.

[15]  Loris Nanni,et al.  An On-Line Signature Verification System Based on Fusion of Local and Global Information , 2005, AVBPA.

[16]  Mario Vento,et al.  Signature Verification: Increasing Performance by a Multi-Stage System , 2000, Pattern Analysis & Applications.

[17]  Samuel Audet,et al.  Offline Signature Verification Using Virtual Support Vector Machines , 2006 .

[18]  Ana Belén Moreno,et al.  Robust off-line signature verification using compression networks and positional cuttings , 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

[19]  I. S. I. Abuhaiba,et al.  Offline Signature Verification Using Graph Matching , 2007 .

[20]  P. Perona,et al.  Visual signature verification using affine arc-length , 1999, Proceedings. 1999 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No PR00149).

[21]  Julian Fiérrez,et al.  An Off-line Signature Verification System Based on Fusion of Local and Global Information , 2004, ECCV Workshop BioAW.