No Detail Found!

Chinese character recognition using support vector machine

Author(s)
ASLINA BAHARUM Faculty of Computing and Informatics,Universiti Malaysia Sabah, Sabah,Malaysia
ROZITA ISMAIL College of Computing and Informatics, Universiti Tenaga Nasional, Putrajaya Campus,,Malaysia
SHALIZA HAYATI A. WAHAB Faculty of Computing and Informatics,Universiti Malaysia Sabah, Sabah,Malaysia
FARHANA DIANA DERIS Faculty of Social Sciences and Humanities,Universiti Teknologi Malaysia,Malaysia
NOORSIDI AIZUDDIN MAT NOOR UTM CRES, Faculty of Built Environment and Surveying,Universiti Teknologi,Malaysia
MOHD SHAREDUWAN MOHD KASIHMUDDIN School of Mathematical Sciences, Universiti Sains Malaysia,Minden, Penang,Malaysia
Abstract
Optical character recognition is the art of scanning and detecting the word in the images so that the machine can identify and classify the character. Chinese characters are one of the world's most widely used writing systems. It is used by more than one-quarter of the world's population in daily communication. Chinese characters can be considered difficult because they have many categories, complex character structures, similarities between characters, and various fonts or writing styles. There are many known machine learning algorithms for character recognition, but not all can classify Chinese characters with high speed and accuracy. Therefore, this paper proposes recognizing Chinese characters using support vector machines. Support vector machines are a classification of two classes widely used in classification. It produces very accurate results for many classes, making it suitable for recognizing Chinese characters.
Publication Details
Page(s) 5335-5340
DOI DOI not available
Published Journal: Journal of Theoretical and Applied Information Technology, Volume: 100, Issue: 17, Year: 2022

Request the full text from PASTIC

Keywords
Support Vector Machine, Feature, Character, Optical Character Recognition (OCR), Classifier
More from Journal of Theoretical and Applied Information Technology
0

Citations

0

Downloads

34

Views

Copyright ©  PASTIC National Center, Islamabad www.pastic.gov.pk