An object centric image retrieval framework using multi-agent model for retrieving non-redundant web images. (2015)

• Record Type: Journal Article
• Authors: Shekhar, Shashi; Singh, Anshy; Agrawal, Subhash Chand
• Is Part Of: International journal of image mining. Volume 1:Number 1(2015)
• Page Start: 4
• Page End: 22
• Publication Date: 2015
• Subjects: 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; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

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.