Content based image retrieval and classification using Speeded-Up Robust Features (SURF) and grouped Bag-of-Visual-Words (BoVW)

Alfanindya, Alexandra and Hashim, Noramiza and Eswaran, Chikannan (2013) Content based image retrieval and classification using Speeded-Up Robust Features (SURF) and grouped Bag-of-Visual-Words (BoVW). In: 2013 International Conference on Technology, Informatics, Management, Engineering, and Environment (TIME-E). IEEE Xplore, pp. 77-82. ISBN 978-1-4673-5730-2

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Abstract

This paper presents a work in progress for a proposed method for Content Based Image Retrieval (CBIR) and Classification. The proposed method makes use of the interest points detector and descriptor called Speeded-Up Robust Features (SURF) combined with Bag-of-Visual-Words (BoVW). The combination yields a good retrieval and classification result when compared to other methods. Moreover, a new dictionary building method in which each group has its own dictionary is also proposed. Our method is tested on the highly diverse COREL1000 database and has shown a more discriminative classification and retrieval result.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > QA75.5-76.95 Electronic computers. Computer science
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 20 Feb 2014 01:56
Last Modified: 20 Feb 2014 01:56
URI: http://shdl.mmu.edu.my/id/eprint/5291

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