Title :
Knowledge model based approach in recognition of on-line Chinese characters
Author :
Chou, Kuo-Sen ; Fan, Kuo-Chin ; Fan, Tzu-I ; Lin, Chang-Keng ; Jeng, Bor-Shenn
fDate :
12/1/1994 12:00:00 AM
Abstract :
A knowledge model-based OCR system is presented for the recognition of on-line connected stroke Chinese characters. In the approach, segment attributes are first extracted to characterize the segment sequence of an unknown character. Next, radical recognition based on model matching is adopted as the coarse classification to reduce the number of candidate characters before detailed matching. Finally, a deviation modeling method is proposed to recognize not only regular writing characters but also characters with stroke-order and stroke-number deviations. The effectiveness of the approach is verified by experiments on the recognition of on-line Chinese characters
Keywords :
image classification; image matching; knowledge based systems; optical character recognition; tree searching; OCR system; coarse classification; connected stroke Chinese characters; deviation modeling method; knowledge model based approach; model matching; online Chinese characters; radical recognition; recognition; regular writing characters; segment attribute; segment sequence; stroke-number deviations; stroke-order deviations; Character recognition; Computer science; Dynamic programming; Helium; Laboratories; Office automation; Optical character recognition software; User interfaces; Writing;
Journal_Title :
Selected Areas in Communications, IEEE Journal on