A Personal Adaptive Module for Handwritten Chinese Charactes Recognition Syatem

• Main Authors: Chuang, Soon-Ching, 莊舜清
• Other Authors: Fu Hsin-Chia
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/75046064813365337702

碩士 === 國立交通大學 === 資訊工程學系 === 84 === This thesis presents an application of statistics theory on off-line adaptivemodule for handwritten Chinese characters recognition. The proposed methodconsists of three components:(1).prior information,(2).feature selection,(3). adaptive module recognition. In order to evaluate the proposed recognition system,we choose 5401 fre-quently used Chinese characters as our domain. The database of each testingand training sample character for the original 5401 classifier was created bythe Computer and Communication Laboratory of Industrial Technology ResearchInstitute. And we select the most 300 frequently used Chinese characterswhich were written by five members of our lab for ten times as the testingand training for the adaptive module. Because the samples for the adaptivemodule were not sepcified,our recognition system could reach a high generalityand user-independence. Experimental results show that, the method improvesrecognition rate from 44.09% to 90.03%.