Recently, a number of methods have been proposed to improve image retrieval accuracy by capturing context
information. These methods try to compensate for the fact that a visually less similar image might be more relevant
because it depicts the same object. We propose a new quick method for refining any pairwise distance metric, it works by
iteratively discovering the object in the image from the most similar images, and then refine the distance metric
accordingly. Test show that our technique improves over the state of art in terms of accuracy over the MPEG7 dataset.