Title :
Font recognition based on global texture analysis
Author :
Zhu, Yong ; Tan, Tieniu ; Wang, Yunhong
Author_Institution :
Coll. of Comput., Georgia Inst. of Technol., Atlanta, GA, USA
fDate :
10/1/2001 12:00:00 AM
Abstract :
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
Keywords :
character sets; document image processing; image texture; optical character recognition; Chinese fonts; English fonts; connected components analysis; content-independent method; document image processing; experiments; font recognition; global texture analysis; image degradation; local typographical features; optical character recognition; texture identification; Character recognition; Feature extraction; Filtering; Gabor filters; Image recognition; Image segmentation; Image texture analysis; Noise robustness; Optical character recognition software; Optical noise;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on