Title: An object centric image retrieval framework using multi-agent model for retrieving non-redundant web images
Authors: Shashi Shekhar; Anshy Singh; Subhash Chand Agrawal
Addresses: Department of Computer Engineering and Applications, GLA University, Mathura-281406, India ' Department of Computer Engineering and Applications, GLA University, Mathura-281406, India ' Department of Computer Engineering and Applications, GLA University, Mathura-281406, India
Abstract: In the current scenario, everybody is surrounded by multimedia devices and its use. The explosion of digital data on internet in various forms like text, audio, images, animations and video has arisen a very challenging question about effective and efficient retrieval of all these information from the web. Retrieving useful and relevant images from the web has become a difficult task. The commercial search engines still depends on textual descriptions attached with images for retrieving images available on the web. In this paper, we have proposed automatic image annotation and image crawling method based on object-based image retrieval algorithms. The proposed framework overcomes the three major problems in case of retrieving user centric images from the web: freshness problem, redundancy problem and multiple object selection problems. The experimental results have been compared with the results of one of the commercial search engine and also shown the performance of image retrieval process on the IAPR TC-12 dataset.
Keywords: web image retrieval; image crawler; image index; semantic image retrieval; image annotation; multi-agent modelling; multi-agent systems; MAS; agent-based systems; non-redundant web images; object-based image retrieval; image freshness; image redundancy; multiple object selection.
International Journal of Image Mining, 2015 Vol.1 No.1, pp.4 - 22
Received: 17 Sep 2014
Accepted: 05 Jan 2015
Published online: 24 Jun 2015 *