Detecting Forged Handwriting with Wavelets and Statistics

Authors

Beverly Lytle, Allegheny CollegeFollow
Caroline Yang, Duke University

Abstract

In this paper, we present a method of analyzing handwriting samples (distinguishing between authentic samples and forgeries) and address the question of whether or not the handwriting of different individuals contains a mathematical signature. The method discussed is a modified version of a similar approach towards art presented in ``A Digital Technique for Art Authentication'' by Lyu et al. We give a short history of art and handwriting forgery and characteristics examined in order to determine authenticity. We also examine the rationale behind the Lyu et al.'s method and the changes that we have made in our application to handwriting analysis.

Author Bio

Beverly Lytle is a senior at Allegheny College. She is a mathematics major and a German studies minor. Caroline Yang is a senior at Duke University. She is a mathematics a major and English minor. Their work together was completed at the REU at Grand Valley State University during the summer of 2005 under Professor Edward Aboufadel.

Faculty Sponsor

Edward Aboufadel

Recommended Citation

Lytle, Beverly and Yang, Caroline (2006) "Detecting Forged Handwriting with Wavelets and Statistics," Rose-Hulman Undergraduate Mathematics Journal: Vol. 7: Iss. 1, Article 8.
Available at: https://scholar.rose-hulman.edu/rhumj/vol7/iss1/8