{"title":"色情视频检测系统的实现","authors":"Zhiyi Qu, Liping Ren, A. Guo, Jing Yu","doi":"10.1109/CISP.2009.5301633","DOIUrl":null,"url":null,"abstract":"Based on the features of video content, this paper addresses the system of detecting pornographic videos. The system makes use of an improved algorithm for shot segmentation based on clustering and then extracts key frames. It converts the detection of video to identification of key frames. We use the skin color detection to detect the key frames which have been extracted. The experimental results show that the method's correct detection is up to 80% and it is an effective method for detecting pornographic videos.","PeriodicalId":263281,"journal":{"name":"2009 2nd International Congress on Image and Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Implementation of Pornographic Videos Detection System\",\"authors\":\"Zhiyi Qu, Liping Ren, A. Guo, Jing Yu\",\"doi\":\"10.1109/CISP.2009.5301633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Based on the features of video content, this paper addresses the system of detecting pornographic videos. The system makes use of an improved algorithm for shot segmentation based on clustering and then extracts key frames. It converts the detection of video to identification of key frames. We use the skin color detection to detect the key frames which have been extracted. The experimental results show that the method's correct detection is up to 80% and it is an effective method for detecting pornographic videos.\",\"PeriodicalId\":263281,\"journal\":{\"name\":\"2009 2nd International Congress on Image and Signal Processing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 2nd International Congress on Image and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISP.2009.5301633\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 2nd International Congress on Image and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISP.2009.5301633","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Implementation of Pornographic Videos Detection System
Based on the features of video content, this paper addresses the system of detecting pornographic videos. The system makes use of an improved algorithm for shot segmentation based on clustering and then extracts key frames. It converts the detection of video to identification of key frames. We use the skin color detection to detect the key frames which have been extracted. The experimental results show that the method's correct detection is up to 80% and it is an effective method for detecting pornographic videos.
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