On Computing Strength of Evidence for Writer Verification

Abstract

The problem of writer verification is to make a decision of whether or not two handwritten documents are written by the same person. Providing a strength of evidence for any such decision is an integral part of the writer verification problem. The strength of evidence should incorporate (i) The amount of information compared in each of the two documents (line/half page/full page etc.), (ii) The nature of content present in the document (same/different content), (iii) Features used for comparison and (iv) The error rate of the model used for making the decision. This paper describes the statistical model used for writer verification and also introduces a mathematical formulation to include the above four mentioned parameters, for calculating strength of evidence of same/different writer. The statistical model uses Gamma and Gaussian densities to parametrically model the distance space distribution arising from comparing ensemble of pairs of documents. The strength of evidence is mapped to a 9-point qualitative scale for the decision; one that is often used by questioned document examiners. Experiments and results show that with increase in information content from just a single word to a full page of document, the verification accuracy of the model increases.