{"title":"Based on Image Salient Features Network Image Retrieval Method","authors":"K. Yan, Ke Feng, Y. Wang, Bo-nian Pan","doi":"10.1109/CIS.2012.72","DOIUrl":null,"url":null,"abstract":"Traditional image retrieval depends on the images embedded in text messages, text description of the limitations of image content, resulting in low quality of image retrieval. The local information extracted image itself, the use of local features LSH image matching algorithm, memory requirements has led to a linear growth. To overcome these shortcomings, then propose the method of image retrieval which based on the network salient features, by screening out the salient features of the frequent appearance of points, with each image feature point matching vectors to generate histogram matching, the use of its similarity to generate the calculation of PageRank, Adjacency matrix for each image to generate a PageRank score. Experimental results show that the algorithm improves the network image retrieval efficiency and accuracy.","PeriodicalId":294394,"journal":{"name":"2012 Eighth International Conference on Computational Intelligence and Security","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Eighth International Conference on Computational Intelligence and Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.2012.72","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Traditional image retrieval depends on the images embedded in text messages, text description of the limitations of image content, resulting in low quality of image retrieval. The local information extracted image itself, the use of local features LSH image matching algorithm, memory requirements has led to a linear growth. To overcome these shortcomings, then propose the method of image retrieval which based on the network salient features, by screening out the salient features of the frequent appearance of points, with each image feature point matching vectors to generate histogram matching, the use of its similarity to generate the calculation of PageRank, Adjacency matrix for each image to generate a PageRank score. Experimental results show that the algorithm improves the network image retrieval efficiency and accuracy.