A two-stage scheme for text detection in video images

  • Authors:

  • Marios Anthimopoulos;Basilis Gatos;Ioannis Pratikakis

  • Affiliations:

  • Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos", 153 10 Athens, Greece;Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos", 153 10 Athens, Greece;Computational Intelligence Laboratory, Institute of Informatics and Telecommunications, National Center for Scientific Research "Demokritos", 153 10 Athens, Greece

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2010

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Abstract

This paper proposes a two-stage system for text detection in video images. In the first stage, text lines are detected based on the edge map of the image leading in a high recall rate with low computational time expenses. In the second stage, the result is refined using a sliding window and an SVM classifier trained on features obtained by a new Local Binary Pattern-based operator (eLBP) that describes the local edge distribution. The whole algorithm is used in a multiresolution fashion enabling detection of characters for a broad size range. Experimental results, based on a new evaluation methodology, show the promising overall performance of the system on a challenging corpus, and prove the superior discriminating ability of the proposed feature set against the best features reported in the literature.