Title :
Character Independent Font Recognition on a Single Chinese Character
Author :
Xiaoqing Ding ; Li Chen ; Tao Wu
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing
Abstract :
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
Keywords :
character recognition; character sets; feature extraction; wavelet transforms; Box-Cox transformation; Chinese character; character identity; character independent font recognition; linear discriminant analysis; quadric distance function; wavelet feature extraction; wavelet transform; Background noise; Character recognition; Feature extraction; Linear discriminant analysis; Optical character recognition software; Optical noise; Prototypes; Robustness; Text recognition; Wavelet transforms; Font recognition; LDA; MQDF.; character independent; single character; wavelet features; Algorithms; Artificial Intelligence; Automatic Data Processing; Computer Graphics; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Information Storage and Retrieval; Pattern Recognition, Automated;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2007.26