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Issue No. 02 - February (2007 vol. 29)
ISSN: 0162-8828
pp: 195-204
Li Chen , IEEE
Tao Wu , IEEE
A novel algorithm for font recognition on a single unknown Chinese character, independent of the identity of the character, is proposed in this paper. We employ a wavelet transform on the character image and extract wavelet features from the transformed image. After a Box-Cox transformation and LDA (Linear Discriminant Analysis) process, the discriminating features for font recognition are extracted and classified through a MQDF (Modified Quadric Distance Function) classifier with only one prototype for each font class. Our experiments show that our algorithm can achieve a recognition rate of 90.28 percent on a single unknown character and 99.01 percent if five characters are used for font recognition. Compared with existing methods, all of which are based on a text block, our method can provide a higher recognition rate and is more flexible and robust, since it is based on a single unknown character. Additionally, our method demonstrates that it is possible to extract subtle yet discriminative signals embedded in a much larger noisy background.
Font recognition, character independent, single character, wavelet features, LDA, MQDF.

X. Ding, T. Wu and L. Chen, "Character Independent Font Recognition on a Single Chinese Character," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 29, no. , pp. 195-204, 2007.
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