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Texture-Based Text Detection in Digital Images with Wavelet Features and Support Vector Machines

  • Marcin Grzegorzek
  • Chen Li
  • Johann Raskatow
  • Dietrich Paulus
  • Natalia Vassilieva
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 226)

Abstract

In this paper we propose to combine region-based and texture-based approaches for text detection in digital images. Our solution is based on a cascade filtering of image regions. First, we apply heuristic filtering to disregard certain non-textual areas. Second, we perform a more precise and expensive texture-based filtering using support vector machines and wavelet-based texture features. We have evaluated our approach with the ICDAR 2003 text locating competition benchmark collection and tools. The experimental results showed competitive performance of our solution by means of recall and precision compared to other text detection approaches participated in ICDAR 2003 and lower computational cost at the same time.

Keywords

Text Detection Wavelet Features Support Vector Machines 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Marcin Grzegorzek
    • 1
  • Chen Li
    • 1
  • Johann Raskatow
    • 2
  • Dietrich Paulus
    • 2
  • Natalia Vassilieva
    • 3
  1. 1.Pattern Recognition GroupUniversity of SiegenSiegenGermany
  2. 2.Active Vision GroupUniversity of Koblenz-LandauLandauGermany
  3. 3.HP LabsSt. PetersburgRussia

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