Exploiting Character Class Information in Forensic Writer Identification

  • Fernando Alonso-Fernandez
  • Julian Fierrez
  • Javier Galbally
  • Javier Ortega-Garcia
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6540)


Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on contour features operating in identification mode (one-to-many) and working at the level of isolated characters. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowercase and uppercase letters), being the particular setup used by the forensic laboratory participating in this work. Three different scenarios for identity modeling are proposed, making use to a different degree of the class information provided by the alphanumeric samples. Results obtained on a database of 30 writers from real forensic documents show that the character class information given by the manual analysis provides a valuable source of improvement, justifying the significant amount of time spent in manual segmentation and labeling by the forensic specialist.


Manual Segmentation Uppercase Letter Trained Operator Contour Feature Handwritten Character 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fernando Alonso-Fernandez
    • 1
  • Julian Fierrez
    • 1
  • Javier Galbally
    • 1
  • Javier Ortega-Garcia
    • 1
  1. 1.Biometric Recognition Group - ATVS, Escuela Politecnica SuperiorUniversidad Autonoma de MadridMadridSpain

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