An improved method for the character recognition based on SVM

Authors:
Hu Chengwen;Zhao Yannan;Wang Jiaxin;Yang Zehong
Affiliations:
Computer Science and Technology Department, Tsinghua University, Beijing, China;Computer Science and Technology Department, Tsinghua University, Beijing, China;Computer Science and Technology Department, Tsinghua University, Beijing, China;Computer Science and Technology Department, Tsinghua University, Beijing, China
Venue:
AIA'06 Proceedings of the 24th IASTED international conference on Artificial intelligence and applications
Year:
2006

Citing 5
Cited 0

A training algorithm for optimal margin classifiers

COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Support-Vector Networks

Machine Learning
High Accuracy Handwritten Chinese Character Recognition by Improved Feature Matching Method

ICDAR '97 Proceedings of the 4th International Conference on Document Analysis and Recognition
Chinese Character Recognition via Gegenbauer Moments

ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
LIBSVM: A library for support vector machines

ACM Transactions on Intelligent Systems and Technology (TIST)

Quantified Score

Hi-index	0.00

Visualization

Abstract

To deal with the character recognition in Chinese vehicle license plate, several feature extraction algorithms are compared in this paper, as well as their performance based on the SVM classifier and the conventional MDC classifier, respectively. The result shows that the combination of Gabor feature and SVM classifier can reach good performance, especially for the Chinese character recognition.