Images Similarity Estimation By Processing Compressed Data
Document Type
Article
Publication Date
5-1-2001
Publication Title
Image and Vision Computing
Volume
19
Issue
7
First page number:
485
Last page number:
500
Abstract
A method is proposed to evaluate the similarity of images compressed by a given digital wavelet transform. The method allows for comparing lossless- or lossy-compressed images. Two features that describe the image structural content, namely edge point locations and edge density, are computed directly from multiscale data. The distance between two images is computed in one- or two-dimensional space, depending on the image type and the choice of features selected for processing. The method facilitates content-based image querying and automatic database retrieval. Additionally, images can be sorted and appropriately indexed with respect to such characteristics as smoothness, texture direction, repetition period and the average number of edge points in spatial period.
Keywords
Content-based image querying; Edge density; Edge points locations; Wavelet-based compression
Disciplines
Electrical and Computer Engineering | Engineering | Signal Processing
Language
English
Permissions
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Repository Citation
Regentova, E.,
Latifi, S.,
Deng, S. L.
(2001).
Images Similarity Estimation By Processing Compressed Data.
Image and Vision Computing, 19(7),
485-500.