Online Signature Verification Based on DCT and Sparse Representation

In this paper, a novel online signature verification technique based on discrete cosine transform (DCT) and sparse representation is proposed. We find a new property of DCT, which can be used to obtain a compact representation of an online signature using a fixed number of coefficients, leading to simple matching procedures and providing an effective alternative to deal with time series of different lengths. The property is also used to extract energy features. Furthermore, a new attempt to apply sparse representation to online signature verification is made, and a novel task-specific method for building overcomplete dictionaries is proposed, then sparsity features are extracted. Finally, energy features and sparsity features are concatenated to form a feature vector. Experiments are conducted on the Sabancı University's Signature Database (SUSIG)-Visual and SVC2004 databases, and the results show that our proposed method authenticates persons very reliably with a verification performance which is better than those of state-of-the-art methods on the same databases.

[1]  Berrin A. Yanikoglu,et al.  Online Signature Verification Using Fourier Descriptors , 2009, EURASIP J. Adv. Signal Process..

[2]  Yunhong Wang,et al.  On-line signature verification using wavelet packet , 2011, 2011 International Joint Conference on Biometrics (IJCB).

[3]  Allen Y. Yang,et al.  Robust Face Recognition via Sparse Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Meng Joo Er,et al.  Illumination compensation and normalization for robust face recognition using discrete cosine transform in logarithm domain , 2006, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[5]  Janez Demsar,et al.  Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..

[6]  Rafal Doroz,et al.  On-Line Signature Recognition Based on Reduced Set of Points , 2011, Computer Recognition Systems 4.

[7]  Yutaka Fukui,et al.  On-Line Signature Verification Based on Discrete Wavelet Domain Adaptive Signal Processing , 2004, ICBA.

[8]  Berrin A. Yanikoglu,et al.  SUSIG: an on-line signature database, associated protocols and benchmark results , 2008, Pattern Analysis and Applications.

[9]  Thomas G. Dietterich.  Approximate Statistical Tests for Comparing Supervised Classification Learning Algorithms , 1998, Neural Computation.

[10]  M. Elad,et al.  $rm K$-SVD: An Algorithm for Designing Overcomplete Dictionaries for Sparse Representation , 2006, IEEE Transactions on Signal Processing.

[11]  A. Bruckstein,et al.  K-SVD : An Algorithm for Designing of Overcomplete Dictionaries for Sparse Representation , 2005 .

[12]  Sharath Pankanti,et al.  Biometrics, Personal Identification in Networked Society: Personal Identification in Networked Society , 1998 .

[13]  Stephen P. Boyd,et al.  An Interior-Point Method for Large-Scale $\ell_1$-Regularized Least Squares , 2007, IEEE Journal of Selected Topics in Signal Processing.

[14]  Toby Berger,et al.  Reliable On-Line Human Signature Verification Systems , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Anil K. Jain,et al.  Fusion of Local and Regional Approaches for On-Line Signature Verification , 2005, IWBRS.

[16]  Quentin Barthelemy,et al.  Shift & 2D Rotation Invariant Sparse Coding for Multivariate Signals , 2012, IEEE Transactions on Signal Processing.

[17]  D. Z. Lejtman,et al.  On-line handwritten signature verification using wavelets and back-propagation neural networks , 2001, Proceedings of Sixth International Conference on Document Analysis and Recognition.

[18]  Loris Nanni,et al.  A novel local on-line signature verification system , 2008, Pattern Recognit. Lett..

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

[20]  Michael Elad,et al.  Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries , 2006, IEEE Transactions on Image Processing.

[21]  Ibrahim El-Henawy,et al.  Online Signature Verification: State of the art , 2005 .

[22]  Michael A. Saunders,et al.  Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..

[23]  Hong Chang,et al.  SVC2004: First International Signature Verification Competition , 2004, ICBA.

[24]  Michael Elad,et al.  Double Sparsity: Learning Sparse Dictionaries for Sparse Signal Approximation , 2010, IEEE Transactions on Signal Processing.

[25]  Anil K. Jain,et al.  On-line signature verification, , 2002, Pattern Recognit..

[26]  Thomas S. Huang,et al.  Image Super-Resolution Via Sparse Representation , 2010, IEEE Transactions on Image Processing.

[27]  Giuseppe Pirlo,et al.  Automatic Signature Verification: The State of the Art , 2008, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[28]  Julian Fiérrez,et al.  HMM-based on-line signature verification: Feature extraction and signature modeling , 2007, Pattern Recognit. Lett..

[29]  Michael R. Lyu,et al.  Spectrum Analysis Based onWindows with Variable Widths for Online Signature Verification , 2006, 18th International Conference on Pattern Recognition (ICPR'06).

[30]  Yunhong Wang,et al.  On-line Signature Verification Using Graph Representation , 2011, 2011 Sixth International Conference on Image and Graphics.

[31]  Bernhard Sick,et al.  Online Signature Verification With Support Vector Machines Based on LCSS Kernel Functions , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[32]  Nidal S. Kamel,et al.  Svd-Based Signature Verification Technique Using Data Glove , 2008, Int. J. Pattern Recognit. Artif. Intell..

[33]  Michael Elad,et al.  From Sparse Solutions of Systems of Equations to Sparse Modeling of Signals and Images , 2009, SIAM Rev..

[34]  Carlos Vivaracho-Pascual,et al.  An efficient low cost approach for on-line signature recognition based on length normalization and fractional distances , 2009, Pattern Recognit..

[35]  Michael Elad,et al.  Audio Inpainting , 2012, IEEE Transactions on Audio, Speech, and Language Processing.

[36]  George Economou,et al.  Online signature verification based on signatures turning angle representation using longest common subsequence matching , 2012, International Journal on Document Analysis and Recognition (IJDAR).

[37]  Berrin A. Yanikoglu,et al.  Identity authentication using improved online signature verification method , 2005, Pattern Recognit. Lett..

[38]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[39]  Zhaoxiang Zhang,et al.  A Survey of On-line Signature Verification , .

[40]  Nannan Yu,et al.  Denoising for Multiple Image Copies through Joint Sparse Representation , 2012, Journal of Mathematical Imaging and Vision.

[41]  Hazem M. Abbas,et al.  Enhanced DTW based on-line signature verification , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[42]  Andréa Vergara da Silva,et al.  Wavelet-Based Compared to Function-Based On-Line Signature Verification , 2002, SIBGRAPI.

[43]  Mohammed J. Alhaddad.  Multiple Classifiers to verify the Online Signature , 2012 .

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

[45]  Ling Guan,et al.  On-line signature verification using global features , 2009, 2009 Canadian Conference on Electrical and Computer Engineering.

[46]  H. N. Prakash,et al.  Online Signature Verification and Recognition: An Approach Based on Symbolic Representation , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[47]  Bernadette Dorizzi,et al.  Online Handwritten Signature Verification , 2009 .

[48]  Marcos Faúndez-Zanuy,et al.  Efficient on-line signature recognition based on multi-section vector quantization , 2010, Pattern Analysis and Applications.

[49]  T. Apostol.  Mathematical Analysis , 1957 .