Title :
A universal method for single character type recognition
Author :
Chen, Li ; Ding, Xiaoqing
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
Character image contains not only the character information, but also the type information. The character´s type information denotes the various category of the character, such as the font families, handwritten or printed, to what language the character belongs, etc. Most of the existent methods for character type recognition are carried out on a group of characters belonging to the same category, and all these methods concentrate on their own specific field. In this paper, a novel universal method for character type recognition is proposed, which is based on a single unknown character and can be used in various fields. We employ a wavelet transform on the character image and extract wavelet features from the transformed image, which are used by a MQDF classifier. Compared with existent methods, our method is much more flexible, robust and effective.
Keywords :
character recognition; feature extraction; image classification; image recognition; wavelet transforms; character image recognition; modified quadratic discriminant function classifier; single character type recognition; wavelet feature extraction; wavelet transform; Character recognition; Data mining; Feature extraction; Handwriting recognition; Histograms; Robustness; Text analysis; Text recognition; Wavelet transforms;
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
Print_ISBN :
0-7695-2128-2
DOI :
10.1109/ICPR.2004.1334141