Title :
Average Fuzzy Direction Based Handwritten Chinese Characters Recognition Approach
Author :
Zhu, Weiping ; Liu, Wei ; Huang, Zhuqing
Author_Institution :
China Jiliang Univ., Hangzhou
Abstract :
Since handwritten Chinese characters´ style is uncertain and differs as people differ, this article brings forward a new Average Fuzzy Direction Code based on weight, so as to conquer traditional fuzzy arithmetic´s shortcoming that is without enough generalization capability; At the same time it improves association rules in data mining and applies it to the process of handwritten Chinese characters´ generalization and picking up of their abstract attributes. Thus exact denotation of handwritten Chinese characters is resolved, and simultaneously it picks up the handwritten Chinese characters´ characteristic and mines improved association rules, and further achieves the purpose of handwritten Chinese characters´ quick recognition. Therefore it resolves traditional pattern identification´s problem of poor adaptability.
Keywords :
data mining; fuzzy set theory; generalisation (artificial intelligence); handwritten character recognition; natural languages; abstract attributes; association rules; average fuzzy direction code; data mining; fuzzy arithmetic; fuzzy direction based; generalization capability; handwritten Chinese characters recognition; Arithmetic; Association rules; Character recognition; Data mining; Educational institutions; Handwriting recognition; Robustness; Writing;
Conference_Titel :
Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on
Conference_Location :
Adelaide, SA
Print_ISBN :
978-0-7695-3090-1
DOI :
10.1109/WKDD.2008.52