G. S. Reddy, P. Sharma, S. Prasanna, C. Mahanta, L. Sharma
{"title":"结合在线和离线阿萨姆斯手写数字识别器","authors":"G. S. Reddy, P. Sharma, S. Prasanna, C. Mahanta, L. Sharma","doi":"10.1109/NCC.2012.6176859","DOIUrl":null,"url":null,"abstract":"This work describes the development of an Assamese handwritten numeral recognizer. Online handwritten numeral recognition system is developed using x, y coordinates as the feature and Hidden Markov Model (HMM) as the modelling technique. Offline handwritten numeral recognition system is developed using vertical projection profile and horizontal projection profile (VPP-HPP), zonal discrete cosine transform (DCT), chain code histogram (CCH) and pixel level information as features and vector quantization (VQ) as the modelling technique. The confusion patterns of online and offline systems are analysed. Based on this, the two systems are further combined to obtain a final numeral recognition system. The combined system exhibits improved performance over the individual approaches, demonstrating the significance of different natures of information present in each mode.","PeriodicalId":178278,"journal":{"name":"2012 National Conference on Communications (NCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"24","resultStr":"{\"title\":\"Combined online and offline assamese handwritten numeral recognizer\",\"authors\":\"G. S. Reddy, P. Sharma, S. Prasanna, C. Mahanta, L. Sharma\",\"doi\":\"10.1109/NCC.2012.6176859\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work describes the development of an Assamese handwritten numeral recognizer. Online handwritten numeral recognition system is developed using x, y coordinates as the feature and Hidden Markov Model (HMM) as the modelling technique. Offline handwritten numeral recognition system is developed using vertical projection profile and horizontal projection profile (VPP-HPP), zonal discrete cosine transform (DCT), chain code histogram (CCH) and pixel level information as features and vector quantization (VQ) as the modelling technique. The confusion patterns of online and offline systems are analysed. Based on this, the two systems are further combined to obtain a final numeral recognition system. The combined system exhibits improved performance over the individual approaches, demonstrating the significance of different natures of information present in each mode.\",\"PeriodicalId\":178278,\"journal\":{\"name\":\"2012 National Conference on Communications (NCC)\",\"volume\":\"34 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"24\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 National Conference on Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2012.6176859\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2012.6176859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combined online and offline assamese handwritten numeral recognizer
This work describes the development of an Assamese handwritten numeral recognizer. Online handwritten numeral recognition system is developed using x, y coordinates as the feature and Hidden Markov Model (HMM) as the modelling technique. Offline handwritten numeral recognition system is developed using vertical projection profile and horizontal projection profile (VPP-HPP), zonal discrete cosine transform (DCT), chain code histogram (CCH) and pixel level information as features and vector quantization (VQ) as the modelling technique. The confusion patterns of online and offline systems are analysed. Based on this, the two systems are further combined to obtain a final numeral recognition system. The combined system exhibits improved performance over the individual approaches, demonstrating the significance of different natures of information present in each mode.