CBIR: Effective Utilization of Image Database
Aashish Joshi, Bipin Parkhe, Mrutunjay Madki, Ruhi Patel, B. P. Singh · AIP conference proceedings · 2010
The aim of this paper is to review the current state of the art in content‐based image retrieval (CBIR), a technique for retrieving images on the basis of automatically‐derived features such as color, texture and shape. Our findings are based both on a review of the relevant literature and few results found during the work in the field. This paper focuses on the problem of texture and shape feature extractions. We investigated texture feature and shape feature for CBIR by successfully combining the Gabor filters and Zernike moments (GF+ZM). GF is used for texture feature extraction and ZM extracts shape features. For color feature, each image added to the collection is analyzed to compute a cooler histogram which shows the proportion of pixels of each color within the image. The color histogram for each image is then stored in the database.