Signature Verification Using Static and Dynamic Features

  • Mayank Vatsa
  • Richa Singh
  • Pabitra Mitra
  • Afzel Noore
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)


A signature verification algorithm based on static and dynamic features of online signature data is presented. Texture and topological features are the static features of a signature image whereas the digital tablet captures in real-time the pressure values, breakpoints, and the time taken to create a signature. 1D – log Gabor wavelet and Euler numbers are used to analyze the textural and topological features of the signature respectively. A multi-classifier decision algorithm combines the results obtained from three feature sets to attain an accuracy of 98.18%.


Comparison Matrix Topological Feature Euler Number Signature Code Signature Verification 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bigun, J., du Buf, J.M.: N-folded symmetries by complex moments in Gabor space and their applications to unsupervised texture segmentation. IEEE Transactions on PAMI 16(1), 80–87 (1994)Google Scholar
  2. 2.
    Brault, J.-J., Plamondon, R.: Segmenting Handwritten Signatures at Their Perceptually Important Points. IEEE Transactions on PAMI 15(9), 953–957 (1993)Google Scholar
  3. 3.
    Daugman, J.: Recognizing Persons by their Iris Patterns. In: Jain, A., Bolle, R., Pankati, S. (eds.) Biometric: Personal Identification in Networked Society, pp. 103–121. Kluwer, Dordrecht (1998)Google Scholar
  4. 4.
    Gonzalez, W.: Digital Image Processing, 2nd edn. Pearson Education, LondonGoogle Scholar
  5. 5.
    Josef, K., Mohamad, H., Duin Robert, W.P., Jiri, M.: On combining classifiers. IEEE Transactions on PAMI 20(3), 226–239 (1998)Google Scholar
  6. 6.
    Rubner, Y., Tomasi, C.: Coalescing Texture Descriptors. In: Proceedings of the ARPA Image Understanding Workshop (1996)Google Scholar
  7. 7.
    Scott, D.C., Jain, A.K., Griess, F.D.: On-line Signature Verification. Pattern Recognition 35(12), 2963–2972 (2002)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Mayank Vatsa
    • 1
  • Richa Singh
    • 1
  • Pabitra Mitra
    • 1
  • Afzel Noore
    • 2
  1. 1.Department of Computer Science & EngineeringIndian Institute of TechnologyKanpurIndia
  2. 2.Lane Department of Computer Science & Electrical Engineering, College of Engineering and Mineral ResourcesWest Virginia UniversityMorgantownUSA

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