Font and function word identification in document recognition
Computer Vision and Image Understanding
Optical Font Recognition Using Typographical Features
IEEE Transactions on Pattern Analysis and Machine Intelligence
Font Recognition Based on Global Texture Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Font Recognition and Contextual Processing for More Accurate Text Recognition
ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Multifont Classification Using Typographical Attributes
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
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Chinese fonts are recognized by a new method based on Empirical Mode Decomposition. Five basic strokes have been selected to characterize the features of Chinese fonts. Based on them, stroke feature sequences of a given text block are calculated. Once decomposed by EMD, the first two Intrinsic Mode Functions corresponding to each stroke feature sequence are used to calculate the stroke energy of all the five basic strokes. These energies are combined with the five averages of the residues to produce a tendimensional feature vector. Finally, the minimum distance classifier is used to recognize the fonts. Experiments show encouraging recognition rates.