{"title":"自动视频文本定位和识别","authors":"A. Saracoglu, A. Alatan","doi":"10.1109/SIU.2006.1659917","DOIUrl":null,"url":null,"abstract":"For the indexing and management of large scale video databases an important tool would be the text in the digital media. In this work, the localization performances of the overlay texts using different feature extraction methods with different classifiers are analyzed. Besides that in order to improve the text recognition rate by using multiple hypothesis obtained from multilevel segmentation and using statistical language model are investigated","PeriodicalId":415037,"journal":{"name":"2006 IEEE 14th Signal Processing and Communications Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Automatic Video Text Localization and Recognition\",\"authors\":\"A. Saracoglu, A. Alatan\",\"doi\":\"10.1109/SIU.2006.1659917\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"For the indexing and management of large scale video databases an important tool would be the text in the digital media. In this work, the localization performances of the overlay texts using different feature extraction methods with different classifiers are analyzed. Besides that in order to improve the text recognition rate by using multiple hypothesis obtained from multilevel segmentation and using statistical language model are investigated\",\"PeriodicalId\":415037,\"journal\":{\"name\":\"2006 IEEE 14th Signal Processing and Communications Applications\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 IEEE 14th Signal Processing and Communications Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIU.2006.1659917\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 IEEE 14th Signal Processing and Communications Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2006.1659917","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
For the indexing and management of large scale video databases an important tool would be the text in the digital media. In this work, the localization performances of the overlay texts using different feature extraction methods with different classifiers are analyzed. Besides that in order to improve the text recognition rate by using multiple hypothesis obtained from multilevel segmentation and using statistical language model are investigated
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