Invariant image retrieval using wavelet maxima moment

Abstract

Wavelets have been shown to be an effective analysis tool for image indexing due to the fact that spatial information and visual features of images could be well captured in just a few dominant wavelet coefficients. A serious problem with current wavelet-based techniques is in the handling of affine transformations in the query image. In this work, to cure the problem of translation variance with wavelet basis transform while keeping a compact representation, the wavelet transform modulus maxima is employed. To measure the similarity between wavelet maxima representations, which is required in the context of image retrieval systems, the difference of moments is used. As a result, each image is indexed by a vector in the wavelet maxima moment space. Those extracted features are shown to be robust in searching for objects independently of position, size, orientation and image background.