Handwritten Signature Verification Using Complementary Statistical Models

@article{McCabe2009HandwrittenSV,
  title={Handwritten Signature Verification Using Complementary Statistical Models},
  author={Alan McCabe and Jarrod Trevathan},
  journal={J. Comput.},
  year={2009},
  volume={4},
  pages={670-680}
}
This paper describes a system for performing handwritten signature verification using complementary statistical models. The system analyses both the static features of a signature (e.g., shape, slant, size), and its dynamic features (e.g., velocity, pen-tip pressure, timing) to form a judgment about the signer’s identity. This approach’s novelty lies in combining output from existing Neural Network and Hidden Markov Model based signature verification systems to improve the robustness of any… 

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