{"title":"一种改进的M-SIFT算法用于不同视角图像的匹配","authors":"Wenchao Hu, W. Zhou, J. Guan","doi":"10.1109/SIPROCESS.2016.7888261","DOIUrl":null,"url":null,"abstract":"In this paper, we propose an affine invariant image matching algorithm, which is based on the well-known SIFT algorithm. Firstly, we use MSER algorithm to detect affine invariant feature regions. Then covariance matrix of an image patch is used to transform anisotropic patches into isotropic patches by rotating and squeezing. Finally, the affine invariant key points on isotropic patches are detected by SIFT algorithm. Experiments show that M-SIFT works well with large affine angle changes and scale changes compared with SIFT algorithm.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A modified M-SIFT algorithm for matching images with different viewing angle\",\"authors\":\"Wenchao Hu, W. Zhou, J. Guan\",\"doi\":\"10.1109/SIPROCESS.2016.7888261\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose an affine invariant image matching algorithm, which is based on the well-known SIFT algorithm. Firstly, we use MSER algorithm to detect affine invariant feature regions. Then covariance matrix of an image patch is used to transform anisotropic patches into isotropic patches by rotating and squeezing. Finally, the affine invariant key points on isotropic patches are detected by SIFT algorithm. Experiments show that M-SIFT works well with large affine angle changes and scale changes compared with SIFT algorithm.\",\"PeriodicalId\":142802,\"journal\":{\"name\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIPROCESS.2016.7888261\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPROCESS.2016.7888261","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A modified M-SIFT algorithm for matching images with different viewing angle
In this paper, we propose an affine invariant image matching algorithm, which is based on the well-known SIFT algorithm. Firstly, we use MSER algorithm to detect affine invariant feature regions. Then covariance matrix of an image patch is used to transform anisotropic patches into isotropic patches by rotating and squeezing. Finally, the affine invariant key points on isotropic patches are detected by SIFT algorithm. Experiments show that M-SIFT works well with large affine angle changes and scale changes compared with SIFT algorithm.
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