{"title":"Fast retrieval on compressed images for internet applications","authors":"M. Albanesi, Alessandro Giancane","doi":"10.1109/CAMP.2000.875970","DOIUrl":null,"url":null,"abstract":"In this paper we present a method to incorporate a content-based retrieval algorithm on compressed images with a digital image transform scheme to achieve a low cost and fast indexing method. The target application is the access and interaction with huge amount of visual data on Internet. The approach exploits a modified Wavelet multiresolution decomposition and reconstruction scheme and a multiresolution algorithm for feature extraction and index generation. The efficacy of the method has been proved by extensive tests on YUV compressed JPEG images and the performance have been compared with other approaches on uncompressed, original images, even with the addition of noise. The results suggest a great opportunity to embed in a unique paradigm a fast retrieval technique and a good compression algorithm of low computational complexity, very suitable for Internet imaging applications.","PeriodicalId":282003,"journal":{"name":"Proceedings Fifth IEEE International Workshop on Computer Architectures for Machine Perception","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Fifth IEEE International Workshop on Computer Architectures for Machine Perception","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMP.2000.875970","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper we present a method to incorporate a content-based retrieval algorithm on compressed images with a digital image transform scheme to achieve a low cost and fast indexing method. The target application is the access and interaction with huge amount of visual data on Internet. The approach exploits a modified Wavelet multiresolution decomposition and reconstruction scheme and a multiresolution algorithm for feature extraction and index generation. The efficacy of the method has been proved by extensive tests on YUV compressed JPEG images and the performance have been compared with other approaches on uncompressed, original images, even with the addition of noise. The results suggest a great opportunity to embed in a unique paradigm a fast retrieval technique and a good compression algorithm of low computational complexity, very suitable for Internet imaging applications.