New Approach Based on Texture and Geometric Features for Text Detection

  • Hinde Anoual
  • Sanaa El Fkihi
  • Abdelilah Jilbab
  • Driss Aboutajdine
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)


Due to the huge amount of data carried by images, it is very important to detect and identify the text region as accurately as possible before performing any character recognition. In this paper we describe a text detection algorithm in complex background. It is based on texture and connected components analysis. First we abstract texture regions which usually contain text. Second, we segment the texture regions into suitable objects; the image is segmented into three classes. Finally, we analyze all connected components present in each binary image according to the three classes with the aim to remove non-text regions. Experiments on a benchmark database show the advantages of the new proposed method compared to another one. Especially, our method is insensitive to complex background, font size and color; and offers high precision (83%) and recall(73%) as well.


Text detection text localization feature extraction texture analysis geometric analysis 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Hinde Anoual
    • 1
  • Sanaa El Fkihi
    • 1
    • 2
  • Abdelilah Jilbab
    • 1
    • 3
  • Driss Aboutajdine
    • 1
  1. 1.LRIT, unité associée au CNRST, FSRMohammed V University AgdalMorocco
  2. 2.ENSIASMohammed V University SoussiRabatMorocco
  3. 3.Rabat-InstitutsENSET, Madinat AL IrfaneRabatMorocco

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