An image retrieval system based on adaptive wavelet lifting
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]|
|Organisation||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.