A HMM-based approach to recognize ultra low resolution anti-aliased words

Authors:
Farshideh Einsele;Rolf Ingold;Jean Hennebert
Affiliations:
Université de Fribourg, Fribourg, Switzerland;Université de Fribourg, Fribourg, Switzerland;Université de Fribourg, Fribourg, Switzerland
Venue:
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Year:
2007

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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.