{"title":"Affine-Invariant Image Retrieval Based on Wavelet Interest Points","authors":"Guiguang Ding, Qionghai Dai, Wenli Xu, Feng Yang","doi":"10.1109/MMSP.2005.248678","DOIUrl":null,"url":null,"abstract":"This paper presents an affine-in variant image retrieval approach based on wavelet-based detector, which uses the space-tree property of the transform coefficients to estimate the interest points. Meanwhile, in order to retrieve images compressed by wavelet algorithm such as JPEG2000, the detector only uses the partial bit-planes of the wavelet coefficients to detect the interest points. To provide affine-invariant image matching, annular color histogram, annular texture histogram and spatial cohesion based on interest points are presented to describe image features. A series of experiments based on an image database consisting of 1000 images are performed to confirm the effectiveness of our method","PeriodicalId":191719,"journal":{"name":"2005 IEEE 7th Workshop on Multimedia Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2005 IEEE 7th Workshop on Multimedia Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MMSP.2005.248678","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper presents an affine-in variant image retrieval approach based on wavelet-based detector, which uses the space-tree property of the transform coefficients to estimate the interest points. Meanwhile, in order to retrieve images compressed by wavelet algorithm such as JPEG2000, the detector only uses the partial bit-planes of the wavelet coefficients to detect the interest points. To provide affine-invariant image matching, annular color histogram, annular texture histogram and spatial cohesion based on interest points are presented to describe image features. A series of experiments based on an image database consisting of 1000 images are performed to confirm the effectiveness of our method