{"title":"基于改进SIFT特征的视频图像检索","authors":"Hui Gao, Yuncheng Du, Yuqin Li, Shuicai Shi","doi":"10.1109/IWISA.2010.5473328","DOIUrl":null,"url":null,"abstract":"This paper presents an algorithm based on SIFT features. It calculates key points in the image and extracts the feature of the image by calculating the key points' orientation and modulus of the gradient. The similarity between two images is computed using Euclidean distance. The experiment shows that the feature is invariant to image scaling translation, rotation, and partly invariant to illumination changes and has a certain affine invariance. It is better than the color feature in the video image retrieval.","PeriodicalId":298764,"journal":{"name":"2010 2nd International Workshop on Intelligent Systems and Applications","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Video Image Retrieval Based on Improved SIFT Features\",\"authors\":\"Hui Gao, Yuncheng Du, Yuqin Li, Shuicai Shi\",\"doi\":\"10.1109/IWISA.2010.5473328\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an algorithm based on SIFT features. It calculates key points in the image and extracts the feature of the image by calculating the key points' orientation and modulus of the gradient. The similarity between two images is computed using Euclidean distance. The experiment shows that the feature is invariant to image scaling translation, rotation, and partly invariant to illumination changes and has a certain affine invariance. It is better than the color feature in the video image retrieval.\",\"PeriodicalId\":298764,\"journal\":{\"name\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 2nd International Workshop on Intelligent Systems and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWISA.2010.5473328\",\"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 2nd International Workshop on Intelligent Systems and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWISA.2010.5473328","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video Image Retrieval Based on Improved SIFT Features
This paper presents an algorithm based on SIFT features. It calculates key points in the image and extracts the feature of the image by calculating the key points' orientation and modulus of the gradient. The similarity between two images is computed using Euclidean distance. The experiment shows that the feature is invariant to image scaling translation, rotation, and partly invariant to illumination changes and has a certain affine invariance. It is better than the color feature in the video image retrieval.
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