Localizing global descriptors for content-based image retrieval

In this paper we explore, extend and simplify the localization of the description ability of the well-established MPEG-7 (SCD, CLD and EHD) and MPEG-7-like (CEDD) global descriptors, which we call the SIMPLE family of descriptors. Sixteen novel descriptors are introduced, that utilize four different sampling strategies for the extraction of image patches to be used as points-of-interest. Designing with focused attention for content based image retrieval tasks, we investigate, analyse and propose the preferred process for the definition of the parameters involved (points detection, description, codebook sizes and descriptors’ weighting strategies). The experimental results conducted on four different image collections reveal an astonishing boost in the retrieval performance of the proposed descriptors compared to their performance in their original global form. Furthermore, they manage to outperform common SIFT and SURF based approaches while they perform comparably if not better, against recent state-of-the-art methods that base their success on much more complex data manipulation.