Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Visually Searching the Web for Content
IEEE MultiMedia
Query by Visual Example - Content based Image Retrieval
EDBT '92 Proceedings of the 3rd International Conference on Extending Database Technology: Advances in Database Technology
Web image retrieval systems with automatic web image annotating techniques
WSEAS Transactions on Information Science and Applications
New method of image retrieval using fractal code on the compression domain
WSEAS TRANSACTIONS on SYSTEMS
IFS fractal code for image retrieval on compression domain
CEA'09 Proceedings of the 3rd WSEAS international conference on Computer engineering and applications
Possibilistic pattern recognition in a digestive database for mining imperfect data
WSEAS TRANSACTIONS on SYSTEMS
A new visualization algorithm for the mandelbrot set
MCBC'09 Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry
Quality evaluation of defects with indefinite or unlimited borders
ICS'09 Proceedings of the 13th WSEAS international conference on Systems
A visual analysis of calculation-paths of the Mandelbrot set
WSEAS Transactions on Computers
On-line content-based image retrieval system using joint querying and relevance feedback scheme
WSEAS Transactions on Computers
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In content-based image retrieval system, describing and extracting image's feature is a key question. An image can be characterized by its fractal codes, and fractal codes can be used as the image's feature to retrieve the images effectively. This paper proposes a novel image retrieval method using information entropy and fractal coding. First, each image in the database is classified by computing information entropy which is compared with a given threshold estimated from the inquired image. Second, the inquired image's fractal codes are generated via Jacquin method, which is applied to the same kind of database images with fractal tenth iteration decoding. Finally, the image retrieval result is obtained by matching the similar Euclidean distance between the inquired image and the iterated decoded image. Experimental results show that compared with the direct image pixels similar matching strategy, our scheme not only reduces retrieval complexity and retrieval time, but also guarantees the retrieval rate. Thus our proposed method is effective and feasible.