Handwritten Signature Verification using Instance Based Learning
For authentication and authorization in legal matter humans are recognized by their Signature. Every human being has their own writing style and hence their signature is used in the financial domain for identity verification. So it is necessary to develop a technique which is efficient in verifying the Handwritten Signature is correct or forge. This paper presents a technique of Handwritten Signature Verification based on Correlation between Handwritten Signature images using feature extracted from it. In this paper, the authors have proposed a method to extract features from scanned image of signatures store it in database.