Title :
Handwriting digit recognition based on extension engineering
Author :
Xiao, Huimin ; Liu, Chen
Author_Institution :
Inf. Sch., Henan Univ. of Finance & Econ., Zhengzhou, China
Abstract :
The complicated training algorithm is needed in the traditional handwriting digits recognition, the complexity of algorithm is very high, and the expansibility to huge database is small. In this paper, the handwriting digit is recognized by means of the extension engineering. The classical domains and the extensional domains of handwriting digit character are constructed. The integrated correlative degrees of the measuring digits and 10 basic digits are calculated and handwriting digits are classified and recognized. According to the calculated correlative degrees and the recognized results, extension engineering is an effective method to handwriting digit recognition.
Keywords :
handwriting recognition; handwritten character recognition; support vector machines; complicated training algorithm; extension engineering; handwriting digit character recognition; support vector machine; Data engineering; Databases; Defense industry; Finance; Forward contracts; Handwriting recognition; Image recognition; Pattern recognition; Support vector machine classification; Support vector machines; Classification; Extension engineering; Handwriting digit recognition; Support vector machine;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5192803
