Content Based Image Retrieval and Classification using speeded-up robust features (SURF) and grouped bag-of-visual-words (GBoVW)

Author

Alfanindya, Alexandra ; Hashim, Noramiza ; Eswaran, Chikannan

Author_Institution

Fac. of Comput. & Inf., Multimedia Univ., Cyberjaya, Malaysia

fYear

2013

fDate

23-26 June 2013

Firstpage

77

Lastpage

82

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.

Keywords

content-based retrieval; image classification; image retrieval; visual databases; CBIR; COREL1000 database; GBoVW; SURF; content-based image classification; content-based image retrieval; dictionary building method; grouped bag-of-visual-words; interest points detector; speeded-up robust features; Accuracy; Databases; Bag-of-Visual-Words (BoVW); Bag-of-Words (BOW); COREL1000; Content Based Image Retrieval (CBIR); Speeded-Up Robust Features (SURF);

fLanguage

English

Publisher

ieee

Conference_Titel

Technology, Informatics, Management, Engineering, and Environment (TIME-E), 2013 International Conference on

Conference_Location

Bandung

Print_ISBN

978-1-4673-5730-2

Type

conf

DOI

10.1109/TIME-E.2013.6611968

Filename

6611968