Image classification using spatial difference descriptor under spatial pyramid matching framework

Abstract

Spatial pyramid matching (SPM) model is an extension of the bagof-visual words (BoW) model for local feature encoding. It firstly partitions the image into increasingly fine sub-regions, and then concatenates the histograms within each sub-region. However, the SPM model does not consider the spatial information differences between sub-regions explicitly. To make use of this information, we exploit a novel descriptor called spatial difference. In the process of promoting the performance of image classification, this descriptor is mainly used to concatenate the histograms of bag-of-visual words model under spatial pyramid matching framework. Finally, we conduct image classification experiments on several public datasets to demonstrate the effectiveness of the proposed scheme.