The Open Cybernetics & Systemics Journal
2014, 8 : 40-43Published online 2014 September 16. DOI: 10.2174/1874110X01408010040
Publisher ID: TOCSJ-8-40
Contextual Distance Refining for Image Retrieval
Computer, Electrical and Mathematical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia.
ABSTRACT
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.