Abstract
Signature recognition is one of the important behavioral biometric trait. Signatures recognition systems can be used to identify precisely user identity by making use of signature information such as x, y variations and pressure from a tablet PC. This makes way for using dynamic, i.e., online handwritten signature based biometric system is more accurate than the static ones, hence can be useful for signature verification applications. In this paper new set of features are proposed for online or dynamic signature recognition. In this research, feature vector and their extraction mechanism is implemented using Webber Local Descriptor (WLD). Thus, helping signature verification applications to detect forgery of signatures. The performance of proposed feature vector is further improved by soft biometric traits of the signature.
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