{"title":"无源毫米波成像隐蔽目标检测","authors":"S. Yeom, Dong-Su Lee, J. Son, Shin-Hwan Kim","doi":"10.1109/IUCS.2010.5666180","DOIUrl":null,"url":null,"abstract":"This paper addresses concealed object detection by passive millimeter wave (MMW) imaging. Passive MMW imaging penetrates into clothing to capture metal and man-made objects. In this paper, we propose a multi-level expectation maximization (EM) method to separate the concealed object from the body area. The performance is evaluated by the average probability of error. We will show that the proposed EM processes segments the object area more accurately than the conventional EM method.","PeriodicalId":108217,"journal":{"name":"2010 4th International Universal Communication Symposium","volume":"58 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Concealed object detection using passive millimeter wave imaging\",\"authors\":\"S. Yeom, Dong-Su Lee, J. Son, Shin-Hwan Kim\",\"doi\":\"10.1109/IUCS.2010.5666180\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses concealed object detection by passive millimeter wave (MMW) imaging. Passive MMW imaging penetrates into clothing to capture metal and man-made objects. In this paper, we propose a multi-level expectation maximization (EM) method to separate the concealed object from the body area. The performance is evaluated by the average probability of error. We will show that the proposed EM processes segments the object area more accurately than the conventional EM method.\",\"PeriodicalId\":108217,\"journal\":{\"name\":\"2010 4th International Universal Communication Symposium\",\"volume\":\"58 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 4th International Universal Communication Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IUCS.2010.5666180\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 4th International Universal Communication Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IUCS.2010.5666180","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Concealed object detection using passive millimeter wave imaging
This paper addresses concealed object detection by passive millimeter wave (MMW) imaging. Passive MMW imaging penetrates into clothing to capture metal and man-made objects. In this paper, we propose a multi-level expectation maximization (EM) method to separate the concealed object from the body area. The performance is evaluated by the average probability of error. We will show that the proposed EM processes segments the object area more accurately than the conventional EM method.