{"title":"WCE视频的分层关键帧提取","authors":"Yixuan Yuan, M. Meng","doi":"10.1109/ICMA.2013.6617922","DOIUrl":null,"url":null,"abstract":"Wireless capsule endoscopy (WCE) is an advanced, patient-friendly imaging technique that enables close examination of the entire small intestine. Since it usually takes hours to review all the video data even by professional clinician, the automatic computer-aided technique is highly demanded. This paper presents a hierarchical methodology for detecting key frames in WCE images. In the first stage, we choose key frames whose changes of information entropies take the local maximum by automatic threshold to cut the images into several sub clots. Then AP clustering method is applied in each clot to extract the second stage key frames. Our method maintains the temporal information and maximizes the content distance. Experimental results demonstrate that the proposed techniques achieve inspiring performance with fidelity 0.9206 and compression ratio 0.9125 on average.","PeriodicalId":335884,"journal":{"name":"2013 IEEE International Conference on Mechatronics and Automation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Hierarchical key frames extraction for WCE video\",\"authors\":\"Yixuan Yuan, M. Meng\",\"doi\":\"10.1109/ICMA.2013.6617922\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless capsule endoscopy (WCE) is an advanced, patient-friendly imaging technique that enables close examination of the entire small intestine. Since it usually takes hours to review all the video data even by professional clinician, the automatic computer-aided technique is highly demanded. This paper presents a hierarchical methodology for detecting key frames in WCE images. In the first stage, we choose key frames whose changes of information entropies take the local maximum by automatic threshold to cut the images into several sub clots. Then AP clustering method is applied in each clot to extract the second stage key frames. Our method maintains the temporal information and maximizes the content distance. Experimental results demonstrate that the proposed techniques achieve inspiring performance with fidelity 0.9206 and compression ratio 0.9125 on average.\",\"PeriodicalId\":335884,\"journal\":{\"name\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 IEEE International Conference on Mechatronics and Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMA.2013.6617922\",\"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 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2013.6617922","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wireless capsule endoscopy (WCE) is an advanced, patient-friendly imaging technique that enables close examination of the entire small intestine. Since it usually takes hours to review all the video data even by professional clinician, the automatic computer-aided technique is highly demanded. This paper presents a hierarchical methodology for detecting key frames in WCE images. In the first stage, we choose key frames whose changes of information entropies take the local maximum by automatic threshold to cut the images into several sub clots. Then AP clustering method is applied in each clot to extract the second stage key frames. Our method maintains the temporal information and maximizes the content distance. Experimental results demonstrate that the proposed techniques achieve inspiring performance with fidelity 0.9206 and compression ratio 0.9125 on average.