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.

Wavelets and other special systems (msc 42C40), Image analysis (msc 62H35), Applications to physics (msc 62P35), Interpolation (msc 65D05), Image processing (compression, reconstruction, etc.) (msc 94A08)
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.