{"title":"Intelligent handwriting Thai Signature Recognition System based on artificial neuron network","authors":"Naruemol Chumuang, M. Ketcham","doi":"10.1109/TENCON.2014.7022415","DOIUrl":null,"url":null,"abstract":"This paper proposes an Intelligent Handwriting Thai Signature Recognition System base on Multilayer Perceptron and Radial Basis Network. The proposed system compose of three main processes, i.e. image pre-processing, feature extraction and Thai signature recognition. In the recognition processes the neural network is used into two stage. First, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) is used to learning handwriting Thai signature and then the trained network will be used for recognizing. Later, RBF is used to decision in final stage. There are 600 images from 10 writers in this experiment then the experimental results show that the proposed method yielded the satisfied results.","PeriodicalId":292057,"journal":{"name":"TENCON 2014 - 2014 IEEE Region 10 Conference","volume":"23 2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"TENCON 2014 - 2014 IEEE Region 10 Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TENCON.2014.7022415","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
This paper proposes an Intelligent Handwriting Thai Signature Recognition System base on Multilayer Perceptron and Radial Basis Network. The proposed system compose of three main processes, i.e. image pre-processing, feature extraction and Thai signature recognition. In the recognition processes the neural network is used into two stage. First, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) is used to learning handwriting Thai signature and then the trained network will be used for recognizing. Later, RBF is used to decision in final stage. There are 600 images from 10 writers in this experiment then the experimental results show that the proposed method yielded the satisfied results.