Image Retrieval Based on Using Hamming Distance

Abstract

The expeditious development of images volume on applications recent creates the need for emergence of new indexing and retrieval tools that facilitate access to relevant need. In this paper, we tried to create a visual vocabulary from phase extraction of descriptors such as color, texture, interest points. The method is to assign a signature to each image in collection. The extraction of signature is based on application of Haar wavelet multiscale, Harris interest points and analyzing color histogram. This signature will undergo a size reduction step by using the PCA (Principal Component Analysis). The signature of each image passes through a stage of binarization. This binary code obtained need using Hamming distance in the similarity matching. Experiments are undertaken into four data sets "Caltech101", "Caltech256", "ImageCLEF 2013" and "ImageCLEF 2014". The obtained results showed effectiveness of our approach.