We propose an algorithm for content-based image retrieval of grayscale images of objects against a background of texture. It employs feature vectors based on moment invariants of detail coefficients produced by the lifting scheme. The prediction filters in this scheme are chosen adaptively: low order (small stencils) near edges and high order elsewhere. The aim is an algorithm that retrieves similar images of an object irrespective of translation, rotation, reflection or re-sizing of the object, lighting conditions and the background texture. We discuss and propose both linear and nonlinear transforms of the feature vectors in order to develop a suitable metric for measuring the distance between them. We present preliminary results with respect to an artificial database.

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CWI. Probability, Networks and Algorithms [PNA]
Signals and Images

Oonincx, P.J, & de Zeeuw, P.M. (2002). An image retrieval system based on adaptive wavelet lifting. CWI. Probability, Networks and Algorithms [PNA]. CWI.