Jarernsri L. MitrpanontYingyot ImprasertMahidol University2018-05-032018-05-032011-07-21Proceedings of the 2011 8th International Joint Conference on Computer Science and Software Engineering, JCSSE 2011. (2011), 160-1652-s2.0-79960395656https://repository.li.mahidol.ac.th/handle/20.500.14594/11781This research enhanced two major processes of the previous work of the off-line Thai handwritten character recognition using hybrid techniques of heuristic rules and neural network system. The proposed functions are mainly in 1) Feature extraction enhancement to improve the feature conflict resolution rule and the specialized neural network-based zigzag feature extraction. These functions are used to refine the conflict features and zigzag patterns; 2) Neural network-based recognition. Specifically, a neural network technique improves the capabilities of the recognition process to handle various styles of writing. The result showed that the additional feature conflict resolution rule could achieve the feature extraction rate of 87.85% (increased 2.13%), the feature extraction rate of the specialized neural network-based zigzag extraction could achieve 90.48% (increased 47.9%) and the recognition rate of the neural network-based recognition which combine both of the two proposed feature extraction functions could achieve 92.78% (increased 9.77%). © 2011 IEEE.Mahidol UniversityComputer ScienceConference PaperSCOPUS10.1109/JCSSE.2011.5930113