Handwritten Signature Verification using Instance Based Learning
 | International Journal of Computer Trends and Technology (IJCTT) |  |
| © March to April Issue 2011 by IJCTT Journal | ||
| Volume-1 Issue-1 | ||
| Year of Publication : 2011 | ||
| Authors :Priya Metri , Ashwinder Kaur |
Priya Metri , Ashwinder Kaur. "Handwritten Signature Verification using Instance Based Learning"International Journal of Computer Trends and Technology (IJCTT),V1(1):52-55 March to April Issue 2011 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.
Abstract— 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 we have proposed a method to extract features from scanned image of signatures store it in database. We correlate features of all sample signatures for each person . Then we have to find a mean value from the correlation value of one person signature then compute deviation from it which is used for verification.
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Keywords— Instance-Based Learning Algorithms, Correlation, Normalization, Signature verification, Feature extraction, Vertical Projection , Horizontal Projection , Diagonal Projection.