Off-line signature verification using structural feature correspondence

This paper presents an off-line signature verification method using a model-based approach. In this method, statistical models are constructed for both pixel distribution and structural layout description. In addition to simple geometric handwriting features, it is proposed to use the directional frontier feature as a structural descriptor of the signature. The statistical verification algorithm based on the geometric handwriting feature is used to accept signatures which closely resemble the reference samples, and to reject random and less skilled forgeries. For the questionable signatures for which the pixel feature judgement is inconclusive, the structural feature verification algorithm is invoked. This algorithm compares the detailed structural correlation between the input and reference signatures in an attempt to detect skilled forgeries. The effectiveness of the approach is evaluated on an experimental signature database.

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