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Text area detection in digital documents images using textural features

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Date
2007
Author
Ar, İlktan
Karsligil, M. Elif
Abstract
In this paper we propose a new texture-based method for extraction of text areas in a complex document image. Gabor filter motivated by the multi-channel filtering approach of Human Visual System (HVS) has been employed to create energy map of the document. In this energy map we assumed that text areas were rich in high frequency components. Connected components (probable text characters) were extracted by binarization of the energy map with Otsu's adaptive threshold method. First non-text components such as pictures lines frames etc. were eliminated by Gabor filtering. As a novel approach remaining non-text components were then eliminated by using character component interval tracing. Elimination that formed in two stage enhanced the success of detecting text area on different kinds of digital documents. © Springer-Verlag Berlin Heidelberg 2007.

Source

Computer Analysis of Images and Patterns

Volume

4673 LNCS

Pages

555-562

URI

https://hdl.handle.net/20.500.12469/1628
https://doi.org/10.1007/978-3-540-74272-2_69

Collections

  • Araştırma Çıktıları / Scopus [1565]
  • Araştırma Çıktıları / WOS [1518]
  • Bilgisayar Mühendisliği / Computer Engineering [188]

Keywords

Character tracing
Document image
Gabor filter
Text area extraction

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