Image database indexing and retrieval using the Fractal Transform
Accessing to large image databases is a huge challenge because of the large amount of data required by images. Therefore automatic and efficient indexing is needed for fast content based retrieval, it alleviates the drawback of any manual annotating.
We propose a method for pattern matching into large image databases based on the Fractal Transform. A mathematical representation is associated to the images of the database. This representation is a set of function parameters resulting from a dedicated fractal compression scheme, and used as an index by a retrieval algorithm. It works entirely in the Fractal transform parameter space of both image and pattern, to obtain performances compatible with an interactive search.
The research engine uses both textures and edges of the pattern. The pattern can be present in the image with different orientations and/or scales by using a multi-compression Fractal representation of the pattern.
This method allows to retrieve in 3 seconds a 64 × 64 pixels pattern in an 100 images (512 × 512 pixels) database, on a SUN Sparc 20 workstation. It can be combined with other indexing and retrieval techniques.
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