Title :
Font recognition based on global texture analysis
Author :
Zhu, Yong ; Tan, Tieniu ; Wang, Yunhong
Author_Institution :
Inst. of Autom., Acad. Sinica, Beijing, China
Abstract :
In this paper, we describe a new texture analysis based approach towards font recognition. Existing methods are typically based on local features that often require connected components analysis. In our new method, we take the document as an image containing some special textures, and font recognition as texture identification. The method is content independent and involves no local feature analysis. Global features are extracted by texture analysis. We apply the well-established 2D Gabor filtering technique to extract such features and a weighted Euclidean distance classifier to fulfil the recognition task. Experiments are made using 6,000 samples of 24 frequently used Chinese fonts (6 typefaces combined with 4 styles) and very promising results are achieved
Keywords :
character sets; document image processing; feature extraction; image texture; optical character recognition; 2D Gabor filtering technique; Chinese fonts; content independent method; document image; font recognition; global feature extraction; global texture analysis; texture identification; weighted Euclidean distance classifier; Automation; Euclidean distance; Feature extraction; Filtering; Flowcharts; Gabor filters; Identity-based encryption; Image texture analysis; Independent component analysis; Laboratories;
Conference_Titel :
Document Analysis and Recognition, 1999. ICDAR '99. Proceedings of the Fifth International Conference on
Conference_Location :
Bangalore
Print_ISBN :
0-7695-0318-7
DOI :
10.1109/ICDAR.1999.791796