Multi-resolution Joint Auto Correlograms: Determining the distance function

Distance function plays a role in content-based image retrieval where the ideal distance function will be able to close the gap between computerised image interpretation and similarity judgment by humans. In this paper, few distance functions in relation to the advancement of Colour Auto Correlogram are studied and compared in order to determine the most suitable distance function for the proposed Multi-resolution Joint Auto Correlograms descriptor. An experiment has been conducted on the SIMPLIcity image database consisting of 1000 images where the precision, recall, and rank of various distance functions are measured. Retrieval results have shown that the L₁-norm has achieved higher precision rate of 78.52% and has able to rank similar images better (a rank of 199) compared to the Generalised Tversky Index distance function.