{"title":"基于DCT特征和文本跟踪的移动机器人文本捕获方法","authors":"Hiroki Shiratori, Hideaki Goto, Hiroaki Kobayashi","doi":"10.1109/ICPR.2006.243","DOIUrl":null,"url":null,"abstract":"When a moving robot tries to find text in the surrounding scene by an onboard video camera, the same text strings appear in many image frames. Since it is a waste of time to recognize the same text strings repeatedly it is necessary to decrease text candidate regions for recognition. This paper presents a text capture system that can look around the environment by an active camera, reducing the number of text strings to be recognized. The text candidate regions are extracted from the images by an improved DCT feature. The text regions are tracked in a video sequence to reduce the text candidate strings. In experiments, we tested 55 images of corridor with seven text strings. The text candidate regions are reduced by 86.8% by our method","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":"{\"title\":\"An Efficient Text Capture Method for Moving Robots Using DCT Feature and Text Tracking\",\"authors\":\"Hiroki Shiratori, Hideaki Goto, Hiroaki Kobayashi\",\"doi\":\"10.1109/ICPR.2006.243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"When a moving robot tries to find text in the surrounding scene by an onboard video camera, the same text strings appear in many image frames. Since it is a waste of time to recognize the same text strings repeatedly it is necessary to decrease text candidate regions for recognition. This paper presents a text capture system that can look around the environment by an active camera, reducing the number of text strings to be recognized. The text candidate regions are extracted from the images by an improved DCT feature. The text regions are tracked in a video sequence to reduce the text candidate strings. In experiments, we tested 55 images of corridor with seven text strings. The text candidate regions are reduced by 86.8% by our method\",\"PeriodicalId\":236033,\"journal\":{\"name\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2006.243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient Text Capture Method for Moving Robots Using DCT Feature and Text Tracking
When a moving robot tries to find text in the surrounding scene by an onboard video camera, the same text strings appear in many image frames. Since it is a waste of time to recognize the same text strings repeatedly it is necessary to decrease text candidate regions for recognition. This paper presents a text capture system that can look around the environment by an active camera, reducing the number of text strings to be recognized. The text candidate regions are extracted from the images by an improved DCT feature. The text regions are tracked in a video sequence to reduce the text candidate strings. In experiments, we tested 55 images of corridor with seven text strings. The text candidate regions are reduced by 86.8% by our method