Abstract :
In this paper, an off-line recognition system based on multifeature and multilevel classification is presented for handwritten Chinese characters. Ten classes of multifeatures, such as peripheral shape features, stroke density features, and stroke direction features, are used in this system. The multilevel classification scheme consists of a group classifier and a five-level character classifier, where two new technologies, overlap clustering and Gaussian distribution selector are developed. Experiments have been conducted to recognize 5,401 daily-used Chinese characters. The recognition rate is about 90 percent for a unique candidate, and 98 percent for multichoice with 10 candidates
Keywords :
Gaussian distribution; feature extraction; optical character recognition; pattern classification; Chinese character recognition; Gaussian distribution selector; OCR; multifeature classification; multilevel classification; off-line recognition; overlap clustering; peripheral shape features; stroke density features; stroke direction features; Character recognition; Computer Society; Dictionaries; Gaussian distribution; Handwriting recognition; Heart; Nonlinear optics; Optical character recognition software; Pattern recognition; Shape;
