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inria-00108410, version 1

Off-Line Writer Verification: A Comparison of a Hidden Markov Model (HMM) and a Gaussian Mixture Model (GMM) Based System

Andreas Schlapbach () 1, Horst Bunke () 1

Tenth International Workshop on Frontiers in Handwriting Recognition (2006)

Abstract: In this paper, we introduce and compare two off-line, text independent writer verification systems. At the core of the first system are Hidden Markov Model (HMM) based recognizers. The second system uses Gaussian Mixture Models (GMMs) to model a person's handwriting. Both systems are evaluated on two test sets consisting of unskillfully forged and skillfully forged text lines, respectively. In this comparison, different confidence measures are considered, based on the raw log-likelihood score, the cohort model approach, and the world model approach.

  • 1:  Institute of Computer Science and Applied Mathematics (IAM)
  • Universität Bern
  • Domain : Computer Science/Document and Text Processing
    Computer Science/Computer Vision and Pattern Recognition
  • Keywords : Writer Verification – Off-Line Handwriting – Hidden Markov Model – Gaussian Mixture Model
  • Comment : http://www.suvisoft.com
 
  • inria-00108410, version 1
  • oai:hal.inria.fr:inria-00108410
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  • Submitted on: Friday, 20 October 2006 16:17:40
  • Updated on: Friday, 20 October 2006 16:22:51