{"title":"高精度定位的模板匹配算法","authors":"Wei Hu, Bo Wang","doi":"10.1109/ICSESS.2017.8343011","DOIUrl":null,"url":null,"abstract":"We propose a novel method for template matching in unconstrained environments. The essence of it is the Multiple Information Matching (MSCE) which combines SSDA, CLD, EHD, a variety of algorithms, a useful, robust and parameter-free similarity measure between two sets of points. Since the SSDA algorithm was easy to influence the image noise and illumination, CLD and EHD are added to make the matching more accurate. Experimental results show that MSCE algorithm is more accurate in matching position.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A template matching algorithm for high precision positioning\",\"authors\":\"Wei Hu, Bo Wang\",\"doi\":\"10.1109/ICSESS.2017.8343011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel method for template matching in unconstrained environments. The essence of it is the Multiple Information Matching (MSCE) which combines SSDA, CLD, EHD, a variety of algorithms, a useful, robust and parameter-free similarity measure between two sets of points. Since the SSDA algorithm was easy to influence the image noise and illumination, CLD and EHD are added to make the matching more accurate. Experimental results show that MSCE algorithm is more accurate in matching position.\",\"PeriodicalId\":179815,\"journal\":{\"name\":\"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSESS.2017.8343011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSESS.2017.8343011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A template matching algorithm for high precision positioning
We propose a novel method for template matching in unconstrained environments. The essence of it is the Multiple Information Matching (MSCE) which combines SSDA, CLD, EHD, a variety of algorithms, a useful, robust and parameter-free similarity measure between two sets of points. Since the SSDA algorithm was easy to influence the image noise and illumination, CLD and EHD are added to make the matching more accurate. Experimental results show that MSCE algorithm is more accurate in matching position.
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