{"title":"泰米尔数字识别","authors":"R. Bremananth, A. Prakash","doi":"10.1109/ARTCom.2009.19","DOIUrl":null,"url":null,"abstract":"This paper describes a system to identify Tamil numerals using a two-stage approach, for a subset of Tamil alphabet or numerals. In the first stage, five sets of each Tamil numeral are trained and in the second stage un-trained Tamil numerals are tested against the trained numerals. We use some pre-processing steps to enhance the images. Resizing has been performed on the images for having a standard size for all the images. Gray-scale conversion has been performed on the images for reducing dimensionality of images, which are required for further processing. Binarization has been performed using a threshold technique to change the pixel value to 0 or 1. After binarization feature extractions of the images are performed as rows, columns signal variations. Training and testing processes are carried out to evaluate the feature extraction.","PeriodicalId":210885,"journal":{"name":"Advances in Recent Technologies in Communication and Computing","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Tamil Numerals Identification\",\"authors\":\"R. Bremananth, A. Prakash\",\"doi\":\"10.1109/ARTCom.2009.19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a system to identify Tamil numerals using a two-stage approach, for a subset of Tamil alphabet or numerals. In the first stage, five sets of each Tamil numeral are trained and in the second stage un-trained Tamil numerals are tested against the trained numerals. We use some pre-processing steps to enhance the images. Resizing has been performed on the images for having a standard size for all the images. Gray-scale conversion has been performed on the images for reducing dimensionality of images, which are required for further processing. Binarization has been performed using a threshold technique to change the pixel value to 0 or 1. After binarization feature extractions of the images are performed as rows, columns signal variations. Training and testing processes are carried out to evaluate the feature extraction.\",\"PeriodicalId\":210885,\"journal\":{\"name\":\"Advances in Recent Technologies in Communication and Computing\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Recent Technologies in Communication and Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ARTCom.2009.19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Recent Technologies in Communication and Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ARTCom.2009.19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper describes a system to identify Tamil numerals using a two-stage approach, for a subset of Tamil alphabet or numerals. In the first stage, five sets of each Tamil numeral are trained and in the second stage un-trained Tamil numerals are tested against the trained numerals. We use some pre-processing steps to enhance the images. Resizing has been performed on the images for having a standard size for all the images. Gray-scale conversion has been performed on the images for reducing dimensionality of images, which are required for further processing. Binarization has been performed using a threshold technique to change the pixel value to 0 or 1. After binarization feature extractions of the images are performed as rows, columns signal variations. Training and testing processes are carried out to evaluate the feature extraction.