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Font recognition based on global texture analysis

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3 Author(s)
Yong Zhu ; Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA ; Tieniu Tan ; Yunhong Wang

We describe a novel texture analysis-based approach toward font recognition. Existing methods are typically based on local typographical features that often require connected components analysis. In our method, we take the document as an image containing some specific textures and regard font recognition as texture identification. The method is content-independent and involves no detailed local feature analysis. Experiments are carried out by using 14000 samples of 24 frequently used Chinese fonts (six typefaces combined with four styles), as well as 32 frequently used English fonts (eight typefaces combined with four styles). An average recognition rate of 99.1 percent is achieved. Experimental results are also included on the robustness of the method against image degradation (e.g., pepper and salt noise) and on the comparison with existing methods

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:23 ,  Issue: 10 )