FIRST: Fractal Indexing and Retrieval SysTem for Image Databases

We present an image indexing method and a system to perform content-based r etrieval in heterogeneous image databases (IDB). The method is based upon t he fractal framework of the iterated function systems (IFS) widely used for image compression. The image index is represented through a vector of nume ric features, corresponding to contractive functions (CF) of the IFS framew ork. The construction of the index vector requires a preliminary processing of the images to select an appropriate set of indexing features (i.e. cont ractive functions). The latter will be successively used to fill in the vec tor components, computed as frequencies by which the selected contractive f unctions appear inside the images. In order to manipulate the index vectors efficiently we use discrete Fourier transform (DFT) to reduce their cardin alities and use a spatial access method (SAM), like R*-tree, to improve sea rch performances. The sound theoretical framework underlying the method ena bled us to formally prove some properties of the index. However, for a comp lete validation of the indexing method, also in terms of effectiveness and efficacy, we performed several experiments on a large collection of images from different domains, which revealed good system performances with a low percentage of false alarms and false dismissals. (C) 1998 Elsevier Science B.V. All rights reserved.