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Published Articles >> Table of Contents >> Abstract
International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06)
pp. 173-176
Handwritten Signature Verification Using Image Invariants and Dynamic Features
Abdullah I. Al-Shoshan, Qassim University, Saudi Arabi
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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CGIV.2006.52
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| Abstract |
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In this paper, a development of automatic signature
classification system is proposed. We have presented offline
and online signature verification system, based on
the signature invariants and its dynamic features. The
proposed system segments each signature based on its
perceptually important points and then, for each
segment, computes a number of features that are scale,
rotation and displacement invariant. The normalized
moments and the normalized Fourier descriptors are
used for this invariancy, while the speed of pen is used as
a dynamic feature of the signature. In both cases the data
acquisition, pre-processing, feature extraction and
comparison steps are analyzed and discussed. Both static
and dynamic features were used as an input to a neural
network. The neural network used for classification is a
multi-layer perception (MLP) with one input layer, one
hidden layer and one output layer. The performance of
the proposed system is presented through simulation
examples.
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 Additional Information
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Citation:
Abdullah I. Al-Shoshan,
"Handwritten Signature Verification Using Image Invariants and Dynamic Features,"
cgiv,
pp. 173-176,
International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06),
2006
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