{"title":"基于局部不变特征的图像匹配算法研究","authors":"Jiaqi Liu, Qiang Wu, Xuwen Li","doi":"10.1109/IIH-MSP.2013.37","DOIUrl":null,"url":null,"abstract":"As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.","PeriodicalId":105427,"journal":{"name":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Research on Image Matching Algorithm Based on Local Invariant Features\",\"authors\":\"Jiaqi Liu, Qiang Wu, Xuwen Li\",\"doi\":\"10.1109/IIH-MSP.2013.37\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.\",\"PeriodicalId\":105427,\"journal\":{\"name\":\"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IIH-MSP.2013.37\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Ninth International Conference on Intelligent Information Hiding and Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIH-MSP.2013.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Image Matching Algorithm Based on Local Invariant Features
As an important foundation for image-guided technology, image matching technique is the key technology of modern war. This paper proposes a new algorithm of affine invariant detector and descriptor of local invariant feature points, starting from feature point detection and description point of view, making up the traditional feature point extraction defects of small number and types. Meantime, proposes an improved similarity measure method based on the previously proposed new feature point detection and description algorithm, it improves the matching accuracy and real-time performance. Finally, compares the experiment results of SURF, SIFT and the improved algorithm proposed in this paper, the experimental results shows that the feature points extracted by the improved algorithm has fully affine invariance, and improved the accuracy and speed of image matching algorithm efficiently.