Paper
8 March 1996 Comparison of wavelet transforms and fractal coding in texture-based image retrieval
Aidong Zhang, Biao Cheng, Raj S. Acharya, Raghu P. Menon
Author Affiliations +
Proceedings Volume 2656, Visual Data Exploration and Analysis III; (1996) https://doi.org/10.1117/12.234661
Event: Electronic Imaging: Science and Technology, 1996, San Jose, CA, United States
Abstract
Image compression techniques based on wavelet and fractal coding have been recognized significantly useful in image texture classification and discrimination. In fractal coding approach, each image is represented by a set of self-transformations through which an approximation of the original image can be reconstructed. These transformations of images can be utilized to distinguish images. The fractal coding technique can be extended to effectively determine the similarity between images. We introduce a joint fractal coding technique, applicable to pairs of images, which can be used to determine the degree of their similarity. Our experimental results demonstrate that fractal code approach is effective for content-based image retrieval. In wavelet transform approach, the wavelet transform decorrelates the image data into frequency domain. Feature vectors of images can be constructed from wavelet transformations, which can also be utilized to distinguish images through measuring distances between feature vectors. Our experiments indicate that this approach is also effective on content-based similarity comparison between images. More specifically, we observe that wavelets transform approach performs more effective on content- based similarity comparison on those images which contain strong texture features, where fractal coding approach performs relatively more uniformly well for various type of images.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Aidong Zhang, Biao Cheng, Raj S. Acharya, and Raghu P. Menon "Comparison of wavelet transforms and fractal coding in texture-based image retrieval", Proc. SPIE 2656, Visual Data Exploration and Analysis III, (8 March 1996); https://doi.org/10.1117/12.234661
Lens.org Logo
CITATIONS
Cited by 20 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Image compression

Fractal analysis

Wavelet transforms

Image retrieval

Wavelets

Databases

Feature extraction

RELATED CONTENT


Back to Top