{"title":"A novel method for multiple-query image retrieval","authors":"M. Taghizadeh, A. Chalechale","doi":"10.1109/SPIS.2015.7422313","DOIUrl":null,"url":null,"abstract":"Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The binary component vector is also generated utilizing low-level feature extraction techniques. The final image retrieval process is performed based on this vector. The experimental results show a better performance and less computation in contrary to previous proposed methods.","PeriodicalId":424434,"journal":{"name":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Signal Processing and Intelligent Systems Conference (SPIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIS.2015.7422313","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Multiple-query image retrieval is usually utilized in order to enhance performance of the image retrieval system with considering single semantic for a query set. So far, multiple-query image retrieval based on different queries has rarely studied. In this work, we intend to address this problem using a binary component vector. This vector indicates distinct components which exist in an image. The binary component vector is also generated utilizing low-level feature extraction techniques. The final image retrieval process is performed based on this vector. The experimental results show a better performance and less computation in contrary to previous proposed methods.