Statistical Features Based Off Line Signature Verification System using Image Processing Techniques

Handwritten signature recognition can be divided into online (or dynamic) and off-line (or static) recognition. Online recognition refers to a process that the signer uses a special pen called a stylus to create his or her signature, producing the pen locations, speeds and pressures, while off-line recognition just deals with signature images acquired by a scanner or a digital camera. In general, offline signature recognition is a challenging problem. Unlike the on-line signature, where dynamic aspects of the signing action are captured directly as the handwriting trajectory, the dynamic information contained in off-line signature is highly degraded. Handwriting features, such as the handwriting order, writing-speed variation, and skillfulness, need to be recovered from the grey-level pixels. The presented work is focused on development of robust algorithm for verification of hand written signature verification. The goal of an automatic signature verification system is to confirm or invalidate the presumed identity of the signer from information obtained during the Recognition of the signature.