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Validating the use of Handwriting as a Biometric and its Forensic Analysis

  • Graham Leedham
  • , Vladimir Pervouchine

Research output: Chapter in Book/Report/Conference proceedingChapterResearch

Abstract

For centuries handwriting (mostly in the form of a handwritten signature or mark) has been used as a means of authorizing documents. The assumption is that handwriting is a unique biometric identifying the writer and signatory. When the authenticity of handwriting or a signature is questioned Forensic Document Examiners are called in to determine whether the handwriting/signature is genuine, forged, or disguised. In recent years the uniqueness or individuality of handwriting has been questioned and the techniques used by Forensic Document Examiners have been found lacking in scientific rigour. In this paper we describe some of the recent work to scientifically determine the individuality of handwriting and validate some of the techniques used by Forensic Document Examiners. The Letter-level microfeatures used by document examiners are studied in detail for three letters and one two-letter grapheme from 165 writers. The results indicate that some of the features used by document examiners do haw the ability to discriminate between writers. The features extracted from graphemes or groups of letters have more discriminative power than features from individual letters. This study shows that handwriting analysis call identify an unknown writer against a set of known writers with a high degree of certainty. It is not possible to determine whether handwriting is a biometric which uniquely identifies an individual.
Original languageEnglish
Title of host publicationProceedings of the International Workshop on Document Analysis
EditorsUmapada Pal, Swapan K Parui, Bidyut B Chaudhuri
Place of PublicationChennai, India
PublisherAllied Publishers Pvt Ltd
Pages175-192
Edition1
ISBN (Print)8177647849, 9788177647846
Publication statusPublished - 2005

Keywords

  • Pattern Recognition and Data Mining
  • Computer Vision
  • Image Processing

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