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Paper   IPM / Cognitive Sciences / 9586
School of Cognitive Sciences
  Title:   Support Vector Machines for Persian Font recognition
  Author(s): 
1.  Ali Borji
2.  Mandana Hamidi
  Status:   In Proceedings
  Proceeding: International Conference on Computer, Electrical, Systems Science, and Engineering (CESSE 2007), Prague, Czech Republic July
  Year:  2007
  Supported by:  IPM
  Abstract:
In this paper we examine the use of global texture analysis based approaches for the purpose of Persian font recognition in machine-printed document images. Most existing methods for font recognition make use of local typographical features and connected component analysis. However derivation of such features is not an easy task. Gabor filters are appropriate tools for texture analysis and are motivated by human visual system. Here we consider document images as textures and use Gabor filter responses for identifying the fonts. The method is content independent and involves no local feature analysis. Two different classifiers Weighted Euclidean Distance and SVM are used for the purpose of classification. Experiments on seven different type faces and four font styles show average accuracy of 85

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