Computer-Assisted Handwriting Analysis: Interaction with Legal Issues in U.S. Courts
IWCF '09 Proceedings of the 3rd International Workshop on Computational Forensics
Off-line hand written input based identity determination using multi kernel feature combination
Pattern Recognition Letters
Role of automation in the examination of handwritten items
Pattern Recognition
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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 verifi- cation problem. The strength of evidence should incorpo- rate (i) The amount of information compared in each of the two documents (line/half page/full page etc.), (ii) The na- ture of content present in the document (same/different con- tent), (iii) Features used for comparison and (iv) The error rate of the model used for making the decision. This pa- per describes the statistical model used for writer verifica- tion and also introduces a mathematical formulation to in- clude the above four mentioned parameters, for calculating strength of evidence of same/different writer. The statisti- cal model uses Gamma and Gaussian densities to paramet- rically 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 ex- aminers. 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.