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Proceedings Paper

Statistical characterization of handwriting characteristics using automated tools
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Paper Abstract

We provide a statistical basis for reporting the results of handwriting examination by questioned document (QD) examiners. As a facet of Questioned Document (QD) examination, the analysis and reporting of handwriting examination suffers from the lack of statistical data concerning the frequency of occurrence of combinations of particular handwriting characteristics. QD examiners tend to assign probative values to specific handwriting characteristics and their combinations based entirely on the examiner's experience and power of recall. The research uses data bases of handwriting samples that are representative of the US population. Feature lists of characteristics provided by QD examiners, are used to determine as to what frequencies need to be evaluated. Algorithms are used to automatically extract those characteristics, e.g., a software tool for extracting most of the characteristics from the most common letter pair th, is functional. For each letter combination the marginal and conditional frequencies of their characteristics are evaluated. Based on statistical dependencies of the characteristics the probability of any given letter formation is computed. The resulting algorithms are incorporated into a system for writer verification known as CEDAR-FOX.

Paper Details

Date Published: 24 January 2011
PDF: 7 pages
Proc. SPIE 7874, Document Recognition and Retrieval XVIII, 78740H (24 January 2011); doi: 10.1117/12.876536
Show Author Affiliations
Gregory R. Ball, State Univ. of New York at Buffalo (United States)
Sargur N. Srihari, State Univ. of New York at Buffalo (United States)

Published in SPIE Proceedings Vol. 7874:
Document Recognition and Retrieval XVIII
Gady Agam; Christian Viard-Gaudin, Editor(s)

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