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Scene Text Recognition and Retrieval for Large Lexicons

  • Udit RoyEmail author
  • Anand Mishra
  • Karteek Alahari
  • C. V. Jawahar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9003)

Abstract

In this paper we propose a framework for recognition and retrieval tasks in the context of scene text images. In contrast to many of the recent works, we focus on the case where an image-specific list of words, known as the small lexicon setting, is unavailable. We present a conditional random field model defined on potential character locations and the interactions between them. Observing that the interaction potentials computed in the large lexicon setting are less effective than in the case of a small lexicon, we propose an iterative method, which alternates between finding the most likely solution and refining the interaction potentials. We evaluate our method on public datasets and show that it improves over baseline and state-of-the-art approaches. For example, we obtain nearly 15 % improvement in recognition accuracy and precision for our retrieval task over baseline methods on the IIIT-5K word dataset, with a large lexicon containing 0.5 million words.

Notes

Acknowledgements

This work was partially supported by the Ministry of Communications and Information Technology, Government of India, New Delhi. Anand Mishra was supported by Microsoft Corporation and Microsoft Research India under the Microsoft Research India PhD fellowship award.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Udit Roy
    • 1
    Email author
  • Anand Mishra
    • 1
  • Karteek Alahari
    • 2
  • C. V. Jawahar
    • 1
  1. 1.CVITIIIT HyderabadHyderabadIndia
  2. 2.Inria, LEAR team, Inria Grenoble Rhône-Alpes, Laboratoire Jean KuntzmannCNRS, Univ. Grenoble AlpesSaint-Martin-d’HéresFrance

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