Multi-font Script Identification Using Texture-Based Features

  • Andrew Busch
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4142)


The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.


Gaussian Mixture Model Document Image Optical Character Recognition Linear Discriminate Function Training Observation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Andrew Busch
    • 1
  1. 1.Griffith UniversityBrisbaneAustralia

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