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A HMM-Based Approach to Recognize Ultra Low Resolution Anti-Aliased Words

  • Farshideh Einsele
  • Rolf Ingold
  • Jean Hennebert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4815)

Abstract

In this paper, we present a HMM based system that is used to recognize ultra low resolution text such as those frequently embedded in images available on the web. We propose a system that takes specifically the challenges of recognizing text in ultra low resolution images into account. In addition to this, we show in this paper that word models can be advantageously built connecting together sub-HMM-character models and inter-character state. Finally we report on the promising performance of the system using HMM topologies which have been improved to take into account the presupposed minimum length of each character.

Keywords

State Sequence Emission Probability Word Image Grid Alignment Adjacent 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 2007

Authors and Affiliations

  • Farshideh Einsele
    • 1
  • Rolf Ingold
    • 1
  • Jean Hennebert
    • 1
  1. 1.Université de Fribourg, Boulevard de Pérolles 90, 1700 FribourgSwitzerland

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