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
Image retrieval method based on entropy and fractal coding
WSEAS TRANSACTIONS on SYSTEMS
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Image retrieval and indexing techniques are important for efficient management of visual database. Many techniques are generally developed based on the associated compression domain. In the fractal domain, a fractal code is a contractive affine mapping that represents a similarity relation between the range block and the domain block in an image. A new algorithm of IFS fractal code for image retrieval on the compression domain is presented in this paper. First, the inquired image and each image in the database are encoded by Jacquin fractal coding. Second, the image fractal feature vector and the distance of fractal code between two images are defined, and the distance between the inquired image and current image in the database are computed one by one. Finally, the preceding n frame images which are the smallest distance sum of fractal code are taken as the retrieval result. Experimental results show that compared with the direct image pixels similar matching strategy, our scheme shortens the retrieval time of compression domain greatly and guarantees the retrieval accuracy. Our proposed method is effective and feasible.