Offline Signature Verification Using the Discrete Radon Transform and a Hidden Markov Model

We developed a system that automatically authenticates offline handwritten signatures using the discrete Radon transform (DRT) and a hidden Markov model (HMM). Given the robustness of our algorithm and the fact that only global features are considered, satisfactory results are obtained. Using a database of 924 signatures from 22 writers, our system achieves an equal error rate (EER) of 18% when only high-quality forgeries (skilled forgeries) are considered and an EER of 4.5% in the case of only casual forgeries. These signatures were originally captured offline. Using another database of 4800 signatures from 51 writers, our system achieves an EER of 12.2% when only skilled forgeries are considered. These signatures were originally captured online and then digitally converted into static signature images. These results compare well with the results of other algorithms that consider only global features.

[1]  Hidetoshi Miike,et al.  An off-line signature verification system using an extracted displacement function , 2002, Pattern Recognit. Lett..

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

[3]  John H. L. Hansen,et al.  Discrete-Time Processing of Speech Signals , 1993 .

[4]  R. Bracewell.  Two-dimensional imaging , 1994 .

[5]  Bin Fang,et al.  Off-line signature verification with generated training samples , 2002, SPIE/COS Photonics Asia.

[6]  J.G.A. Dolfing,et al.  Handwriting recognition and verification : a hidden Markov approach , 1998 .

[7]  Gopal Gupta,et al.  A Review of Dynamic Handwritten Signature Verification , 1997 .

[8]  Y. Y. TANG,et al.  Offline Signature Verification by the Analysis of Cursive Strokes , 2001, Int. J. Pattern Recognit. Artif. Intell..

[9]  Kosin Chamnongthai,et al.  Off-line signature recognition using parameterized Hough transform , 1999, ISSPA '99. Proceedings of the Fifth International Symposium on Signal Processing and its Applications (IEEE Cat. No.99EX359).

[10]  Flávio Bortolozzi,et al.  A Simple Methodology to Bankcheck Segmentation , 1997, BSDIA.

[11]  Sargur N. Srihari,et al.  On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  Hong-Yuan Mark Liao,et al.  Wavelet-Based Off-Line Handwritten Signature Verification , 1999, Comput. Vis. Image Underst..

[13]  Réjean Plamondon,et al.  Automatic signature verification and writer identification - the state of the art , 1989, Pattern Recognit..

[14]  F. Prêteux,et al.  Off-line signature verification by local granulometric size distributions , 1997 .

[15]  Alessandro L. Koerich,et al.  Automatic Extraction of Filled-in Information from Bankchecks Based on Prior Knowledge about Layout Structure , 1997, BSDIA.

[16]  Réjean Plamondon,et al.  Automatic Signature Verification: The State of the Art - 1989-1993 , 1994, Int. J. Pattern Recognit. Artif. Intell..

[17]  Azriel Rosenfeld,et al.  Forgery Detection by Local Correspondence , 2001, Int. J. Pattern Recognit. Artif. Intell..

[18]  Robert Sabourin,et al.  Off-line Identification With Handwritten Signature Images: Survey and Perspectives , 1992 .

[19]  Y. K. Wong,et al.  Offline signature verification with generated training samples , 2002 .

[20]  Ruowei Zhou,et al.  Antiforgery: a novel pseudo-outer product based fuzzy neural network driven signature verification system , 2002, Pattern Recognit. Lett..

[21]  Roland Auckenthaler,et al.  Score Normalization for Text-Independent Speaker Verification Systems , 2000, Digit. Signal Process..

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

[23]  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.

[24]  A. El-Yacoubi,et al.  Off-line signature verification using HMMs and cross-validation , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[25]  Réjean Plamondon,et al.  Extraction of signatures from check background based on a filiformity criterion , 1998, IEEE Trans. Image Process..

[26]  Lawrence R. Rabiner,et al.  A tutorial on hidden Markov models and selected applications in speech recognition , 1989, Proc. IEEE.