International Journal of Computer
Trends and Technology

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Volume 1 | Issue 1 | Year 2011 | Article Id. IJCTT-V1I1P12 | DOI : https://doi.org/10.14445/22312803/IJCTT-V1I1P12

Handwritten Signature Verification using Instance Based Learning

Priya Metri , Ashwinder Kaur

Citation :

Priya Metri , Ashwinder Kaur, "Handwritten Signature Verification using Instance Based Learning," International Journal of Computer Trends and Technology (IJCTT), vol. 1, no. 1, pp. 52-55, 2011. Crossref, https://doi.org/10.14445/22312803/IJCTT-V1I1P12

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.

Keywords

Instance-Based Learning Algorithms, Correlation, Normalization, Signature verification, Feature extraction, Vertical Projection , Horizontal Projection , Diagonal Projection.

References

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