A novel image retrieval based on rectangular spatial histograms of visual words

Content-based image retrieval (CBIR) provides a solution to search the images that are similar to a query image. From last few years, the bag-of-visual-words (BoVW) model gained significance and improved the performance of CBIR. In a standard BoVW model, an image is represented as an order-less histogram of visual words, by ignoring the spatial layout of the image. The spatial layout carries significant information that can enhance the image retrieval accuracy. In this paper, we present a novel method of image representation, which is based on the construction of histograms over two rectangular regions of an image. Division of the image into two rectangular regions at the time of construction of histograms adds the spatial information to the BoVW model. The proposed image representation uses separate visual words for upper and lower rectangular regions of an image. The experimental analysis carriedout on two image datasets validates that the proposed image representation based on the division of an image into histograms of rectangles increases the performance of image retrieval.