Topological and textural features for off-line signature verification based on artificial immune algorithm

This work presents a new system for off-line handwritten signature verification. Specifically, Artificial Immune Recognition System (AIRS) is employed to achieve the verification task. Also, to provide a robust signature character-ization, two new features are used. The first data feature is the Orthogonal Combination of Local Binary Patterns (OC-LBP), which aims to reduce the size of LBP histogram while keeping the same efficiency. In addition, we propose a topological feature that is based on the image Longest-Run-Features (LRF). The proposed features are evaluated comparatively to the state of the art methods. The results obtained for CEDAR dataset, highlight the efficiency of the proposed system.

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

[2]  Walmir M. Caminhas,et al.  A novel Artificial Immune System for fault behavior detection , 2011, Expert Syst. Appl..

[3]  R. Larkins,et al.  Adaptive Feature Thresholding for off-line signature verification , 2008, 2008 23rd International Conference Image and Vision Computing New Zealand.

[4]  Jonathan Timmis,et al.  Artificial Immune Recognition System (AIRS): An Immune-Inspired Supervised Learning Algorithm , 2004, Genetic Programming and Evolvable Machines.

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

[6]  Jesús Francisco Vargas-Bonilla,et al.  Off-line signature verification based on grey level information using texture features , 2011, Pattern Recognit..

[7]  A. N. Rajagopalan,et al.  Off-line signature verification using DTW , 2007, Pattern Recognit. Lett..

[8]  Lois C. Boggess,et al.  Artificial Immune Systems for Classification : Some Issues , 2002 .

[9]  G. Pirlo,et al.  Signature Verification by Multiple Reference Sets , 2008 .

[10]  A. B. Watkins,et al.  A resource limited artificial immune classifier , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[11]  Liming Chen,et al.  Image region description using orthogonal combination of local binary patterns enhanced with color information , 2013, Pattern Recognit..

[12]  Halife Kodaz,et al.  Medical application of information gain based artificial immune recognition system (AIRS): Diagnosis of thyroid disease , 2009, Expert Syst. Appl..

[13]  Di Huang,et al.  Local Binary Patterns and Its Application to Facial Image Analysis: A Survey , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[14]  Bhabatosh Chanda,et al.  A writer-independent off-line signature verification system based on signature morphology , 2010, IITM '10.

[15]  Jesús Francisco Vargas-Bonilla,et al.  Off-line Signature Verification Based on Gray Level Information Using Wavelet Transform and Texture Features , 2010, 2010 12th International Conference on Frontiers in Handwriting Recognition.

[16]  Hassiba Nemmour,et al.  Off-line signature verification using artificial immune recognition system , 2013, 2013 International Conference on Electronics, Computer and Computation (ICECCO).

[17]  Jesús Francisco Vargas-Bonilla,et al.  Robustness of Offline Signature Verification Based on Gray Level Features , 2012, IEEE Transactions on Information Forensics and Security.

[18]  Mahantapas Kundu,et al.  A statistical-topological feature combination for recognition of handwritten numerals , 2012, Appl. Soft Comput..

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

[20]  Bhabatosh Chanda,et al.  Writer-independent off-line signature verification using surroundedness feature , 2012, Pattern Recognit. Lett..

[21]  Flávio Bortolozzi,et al.  A comparison of SVM and HMM classifiers in the off-line signature verification , 2005, Pattern Recognit. Lett..

[22]  Mahantapas Kundu,et al.  Complementary Features Combined in a MLP-based System to Recognize Handwritten Devnagari Character , 2011, J. Inf. Hiding Multim. Signal Process..

[23]  Jing Wang,et al.  An English Letter Recognition Algorithm Based Artificial Immune , 2009, International Symposium on Neural Networks.

[24]  Lingxi Peng,et al.  A handwritten character recognition algorithm based on artificial immune , 2010, 2010 International Conference on Computer Application and System Modeling (ICCASM 2010).

[25]  Matti Pietikäinen,et al.  A comparative study of texture measures with classification based on featured distributions , 1996, Pattern Recognit..

[26]  Enrique Frías-Martínez,et al.  Support vector machines versus multi-layer perceptrons for efficient off-line signature recognition , 2006, Eng. Appl. Artif. Intell..

[27]  Yu Yang.  Application of artificial immune system in handwritten Russian uppercase character recognition , 2011, 2011 International Conference on Computer Science and Service System (CSSS).

[28]  Matti Pietikäinen,et al.  Computer Vision Using Local Binary Patterns , 2011, Computational Imaging and Vision.