Xinwei Wang, Dongmei Li, Shaobin Li, Yuzhen Sun, Shanzhen Lan
{"title":"基于显著性检测的电视角标自适应阈值分割算法","authors":"Xinwei Wang, Dongmei Li, Shaobin Li, Yuzhen Sun, Shanzhen Lan","doi":"10.1109/IMCCC.2015.400","DOIUrl":null,"url":null,"abstract":"TV corner-logo is widely used in current video program, and becomes one of the hot spots in information extraction and analysis. TV corner-logo detection and segmentation algorithm is important for information extraction. In this paper, we presented an adaptive threshold segmentation algorithm, based on the combined time-averaged edge detection and saliency detection, to effectively separate and extract the TV corner-logo from the video sequence. First, we applied Canny operator to detect edges and then calculate the weighted average edge of ten frames, so as to get the time-averaged edge image. Then we combine the time-averaged edge image with the saliency map to get a more accurate segmentation. Finally, we used the adaptive threshold segmentation algorithm to separate the corner-logo. Experimental results show that, this method can effectively detect and separate the corner-logo from the background.","PeriodicalId":438549,"journal":{"name":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"TV Corner-Logo Adaptive Threshold Segmentation Algorithm Based on Saliency Detection\",\"authors\":\"Xinwei Wang, Dongmei Li, Shaobin Li, Yuzhen Sun, Shanzhen Lan\",\"doi\":\"10.1109/IMCCC.2015.400\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"TV corner-logo is widely used in current video program, and becomes one of the hot spots in information extraction and analysis. TV corner-logo detection and segmentation algorithm is important for information extraction. In this paper, we presented an adaptive threshold segmentation algorithm, based on the combined time-averaged edge detection and saliency detection, to effectively separate and extract the TV corner-logo from the video sequence. First, we applied Canny operator to detect edges and then calculate the weighted average edge of ten frames, so as to get the time-averaged edge image. Then we combine the time-averaged edge image with the saliency map to get a more accurate segmentation. Finally, we used the adaptive threshold segmentation algorithm to separate the corner-logo. Experimental results show that, this method can effectively detect and separate the corner-logo from the background.\",\"PeriodicalId\":438549,\"journal\":{\"name\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"volume\":\"214 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMCCC.2015.400\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Fifth International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCCC.2015.400","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
TV Corner-Logo Adaptive Threshold Segmentation Algorithm Based on Saliency Detection
TV corner-logo is widely used in current video program, and becomes one of the hot spots in information extraction and analysis. TV corner-logo detection and segmentation algorithm is important for information extraction. In this paper, we presented an adaptive threshold segmentation algorithm, based on the combined time-averaged edge detection and saliency detection, to effectively separate and extract the TV corner-logo from the video sequence. First, we applied Canny operator to detect edges and then calculate the weighted average edge of ten frames, so as to get the time-averaged edge image. Then we combine the time-averaged edge image with the saliency map to get a more accurate segmentation. Finally, we used the adaptive threshold segmentation algorithm to separate the corner-logo. Experimental results show that, this method can effectively detect and separate the corner-logo from the background.