{"title":"移动车辆上的文本标记检测","authors":"R. Kasturi","doi":"10.1109/ICDAR.2003.1227696","DOIUrl":null,"url":null,"abstract":"Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to be caused by text. The method is tested on a captured video of a typical street scene.","PeriodicalId":249193,"journal":{"name":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","volume":"250 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Detection of text marks on moving vehicles\",\"authors\":\"R. Kasturi\",\"doi\":\"10.1109/ICDAR.2003.1227696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to be caused by text. The method is tested on a captured video of a typical street scene.\",\"PeriodicalId\":249193,\"journal\":{\"name\":\"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.\",\"volume\":\"250 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-08-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2003.1227696\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Seventh International Conference on Document Analysis and Recognition, 2003. Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2003.1227696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Vehicle text marks are unique features which are useful for identifying vehicles in video surveillance applications. We propose a method for finding such text marks. An existing text detection algorithm is modified such that detection is increased and made more robust to outdoor conditions. False alarm is reduced by introducing a binary image test which remove detections that are not likely to be caused by text. The method is tested on a captured video of a typical street scene.
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