The Ministry of Interior in Qatar raised their need for a program to help them in the identification of writers of unknown documents. This project aims to develop a solution to satisfy these requirements. Another problem of writer identification arises frequently in the court of justice in Qatar, where one must come to a conclusion about the authenticity of a document (e.g. a will). It also arises in Qatari banks for signature verification, or in some institutes which analyze texts of former authors, and are interested in the genetics of these texts, as for example the identification of the various writers who took part in the drafting of a manuscript or who made corrections.
We will develop new methods for Arabic handwriting image enhancement using High Boost filtering with a view to lead to efficient image binarization. As a starting point, we will use methods employed by current fingerprint methods. We will investigate a number of approaches using simple and more complex classifiers such as k-NN, conceptual method and Kohonen neural networks and analyze their performances in terms of classification accuracy and speed.
Benefits are also expected to accrue for the PIs in terms of collegiality and productivity, and encouraging of technology makers to look to Qatar as a potential hotbed for education and research.