<title>Image indexing using translation and scale-invariant moments and wavelets</title>

Abstract

Histogram comparison is a popular technique for image indexing. Given a query image, histogram-based techniques can retrieve similar images from a database, which were acquired under similar illumination levels. However, these techniques fail when images are acquired under different illumination conditions. In this paper, we propose two novel histogram-based techniques which are robust to the changes in illumination. First, we propose to employ moments of the image histogram which are invariant to translation and scaling of image gray levels. Secondly, we propose to compare the parameters of histograms of the wavelet subbands for indexing. These parameters are modified appropriately to counter the effect of changes in illumination. The proposed techniques are computationally inexpensive and can be easily integrated within a wavelet-based image coder.