{"title":"个人图像集合中的文本检测","authors":"C. Tran, R. Wijnhoven, P. D. De with","doi":"10.1109/ICCE.2011.5722905","DOIUrl":null,"url":null,"abstract":"We present a novel text detection technique for the application of image annotation in databases of consumer pictures and videos. Images are annotated using information only from the picture itself, as a regular consumer would do. We present results using the challenging public ICDAR2003 dataset and show that our algorithm is competitive with respect to state-of-the-art.","PeriodicalId":256368,"journal":{"name":"2011 IEEE International Conference on Consumer Electronics (ICCE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Text detection in personal image collections\",\"authors\":\"C. Tran, R. Wijnhoven, P. D. De with\",\"doi\":\"10.1109/ICCE.2011.5722905\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a novel text detection technique for the application of image annotation in databases of consumer pictures and videos. Images are annotated using information only from the picture itself, as a regular consumer would do. We present results using the challenging public ICDAR2003 dataset and show that our algorithm is competitive with respect to state-of-the-art.\",\"PeriodicalId\":256368,\"journal\":{\"name\":\"2011 IEEE International Conference on Consumer Electronics (ICCE)\",\"volume\":\"44 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Consumer Electronics (ICCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCE.2011.5722905\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Consumer Electronics (ICCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCE.2011.5722905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a novel text detection technique for the application of image annotation in databases of consumer pictures and videos. Images are annotated using information only from the picture itself, as a regular consumer would do. We present results using the challenging public ICDAR2003 dataset and show that our algorithm is competitive with respect to state-of-the-art.
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