{"title":"结合水平和垂直投影特征提取技术的古穆克手写字符识别","authors":"M. K. Mahto, K. Bhatia, R. Sharma","doi":"10.1109/ICACEA.2015.7164646","DOIUrl":null,"url":null,"abstract":"Despite the advancements in Optical Character Recognition (OCR) technologies, problem of Indic script character recognition remains challenging. Especially in case of handwritten characters the challenges are even more. In this work, we focus on off-line recognition of handwritten characters of Gurmukhi, an Indic script commonly used in state of Punjab in India. As a part of this work, we collected a Gurmukhi character dataset of 3500 images. This dataset is collected from 10 writers. We propose a combined horizontal and vertical projection feature extraction scheme for recognition of Gurmukhi characters. We have tested our method on the collected dataset and achieved a high character recognition accuracy of 98.06%.","PeriodicalId":202893,"journal":{"name":"2015 International Conference on Advances in Computer Engineering and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Combined horizontal and vertical projection feature extraction technique for Gurmukhi handwritten character recognition\",\"authors\":\"M. K. Mahto, K. Bhatia, R. Sharma\",\"doi\":\"10.1109/ICACEA.2015.7164646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Despite the advancements in Optical Character Recognition (OCR) technologies, problem of Indic script character recognition remains challenging. Especially in case of handwritten characters the challenges are even more. In this work, we focus on off-line recognition of handwritten characters of Gurmukhi, an Indic script commonly used in state of Punjab in India. As a part of this work, we collected a Gurmukhi character dataset of 3500 images. This dataset is collected from 10 writers. We propose a combined horizontal and vertical projection feature extraction scheme for recognition of Gurmukhi characters. We have tested our method on the collected dataset and achieved a high character recognition accuracy of 98.06%.\",\"PeriodicalId\":202893,\"journal\":{\"name\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Advances in Computer Engineering and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICACEA.2015.7164646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advances in Computer Engineering and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICACEA.2015.7164646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Combined horizontal and vertical projection feature extraction technique for Gurmukhi handwritten character recognition
Despite the advancements in Optical Character Recognition (OCR) technologies, problem of Indic script character recognition remains challenging. Especially in case of handwritten characters the challenges are even more. In this work, we focus on off-line recognition of handwritten characters of Gurmukhi, an Indic script commonly used in state of Punjab in India. As a part of this work, we collected a Gurmukhi character dataset of 3500 images. This dataset is collected from 10 writers. We propose a combined horizontal and vertical projection feature extraction scheme for recognition of Gurmukhi characters. We have tested our method on the collected dataset and achieved a high character recognition accuracy of 98.06%.