| Summary: | The paper describes the development of a handwritten signature verification system incorporating pen pressure of signature path, time duration of the signing procedure, velocity profile of signature and position of signature shape. The handwritten signals have been captured and digitized using a tablet. The main features of the proposed signature verification system are the dynamically update of handwritten signature, retries capability in verification, application of tolerance bands and threshold values, development of user friendly Graphic User Interface, application of Common Time Axes and verification of signatures using a class of a multilayer feed-forward neural network. A novel algorithm has been applied that provides the ability to produce consistent and high accuracy verification result and maintain the speed of verification. The system has yielded 1.33% of False Reject Rate and 0% False Acceptation Rate with the verification using random forgery signatures.
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