{"title":"图像遮挡作为一个模糊推理问题","authors":"T. Law, H. Itoh, H. Seki","doi":"10.1109/FUZZY.1995.409959","DOIUrl":null,"url":null,"abstract":"The analysis of images which include partially occluded objects must necessarily deal with incomplete information. Fuzzy reasoning is a natural tool for such an application. In this paper, we formulate a method using fuzzy reasoning to recognize various instances of occlusion. The method makes use of image grey levels, triple point incident angles, and curvature of completed objects to evaluate candidate configurations. Furthermore, we implement this method and evaluate it on real test images.<<ETX>>","PeriodicalId":150477,"journal":{"name":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Image occlusions as a fuzzy reasoning problem\",\"authors\":\"T. Law, H. Itoh, H. Seki\",\"doi\":\"10.1109/FUZZY.1995.409959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The analysis of images which include partially occluded objects must necessarily deal with incomplete information. Fuzzy reasoning is a natural tool for such an application. In this paper, we formulate a method using fuzzy reasoning to recognize various instances of occlusion. The method makes use of image grey levels, triple point incident angles, and curvature of completed objects to evaluate candidate configurations. Furthermore, we implement this method and evaluate it on real test images.<<ETX>>\",\"PeriodicalId\":150477,\"journal\":{\"name\":\"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FUZZY.1995.409959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1995 IEEE International Conference on Fuzzy Systems.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FUZZY.1995.409959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The analysis of images which include partially occluded objects must necessarily deal with incomplete information. Fuzzy reasoning is a natural tool for such an application. In this paper, we formulate a method using fuzzy reasoning to recognize various instances of occlusion. The method makes use of image grey levels, triple point incident angles, and curvature of completed objects to evaluate candidate configurations. Furthermore, we implement this method and evaluate it on real test images.<>
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