K. Woraratpanya, Pimlak Boonchukusol, Y. Kuroki, Yasushi Kato
{"title":"改进了自然场景的泰语文本检测","authors":"K. Woraratpanya, Pimlak Boonchukusol, Y. Kuroki, Yasushi Kato","doi":"10.1109/ICITEED.2013.6676227","DOIUrl":null,"url":null,"abstract":"Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.","PeriodicalId":204082,"journal":{"name":"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Improved Thai text detection from natural scenes\",\"authors\":\"K. Woraratpanya, Pimlak Boonchukusol, Y. Kuroki, Yasushi Kato\",\"doi\":\"10.1109/ICITEED.2013.6676227\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.\",\"PeriodicalId\":204082,\"journal\":{\"name\":\"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEED.2013.6676227\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEED.2013.6676227","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thai text detection from natural scenes is still a challenging task for language translation applications, since there are many unsolved issues. Furthermore, the existing related works cannot completely detect Thai text. The main reason is that Thai text layout has vowels and tonal marks that differ from other languages. This paper proposes an approach to detect Thai text from natural scenes. The approach consists of two main procedures. (i) Fast boundary clustering algorithm decomposes scene features into multilayers, so that it is faster and easier to analyze Thai text characters. (ii) Modified connected component analysis method is applied to such scene features in order to detect Thai text boundaries. Based on 150 test images with 4,920 characters, the experimental results demonstrate that the proposed approach achieves the high average precision and recall, 0.80 and 0.90.