Multi-feature Method: An Integrated Content Based Image Retrieval System

Author

Liu, Chen ; Wei, Zhou

Author_Institution

Dept. of Electron. & Inf. Eng., Central China Normal Univ., Wuhan, China

fYear

2011

fDate

22-23 Oct. 2011

Firstpage

43

Lastpage

46

Abstract

The process of retrieving desired or similar images from a large collection of images on the basis of features is referred as Content Based Image Retrieval (CBIR). In this paper, a integrated CBIR system is proposed using combined features and weighted similarity. The features include visual features of color, texture and shape and key text metadata. Some experimental simulations have been presented to show the accuracy and efficiency of the proposed retrieval method.

Keywords

content-based retrieval; feature extraction; image colour analysis; image retrieval; image texture; meta data; color visual features; combined features; integrated CBIR system; integrated content based image retrieval system; key text metadata; multifeature method; shape features; texture features; weighted similarity; Color; Histograms; Image color analysis; Image edge detection; Image retrieval; Shape; CBIR; QBIC; feature retrieval; multi-feature;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligence Information Processing and Trusted Computing (IPTC), 2011 2nd International Symposium on

Conference_Location

Hubei

Print_ISBN

978-1-4577-1130-5

Type

conf

DOI

10.1109/IPTC.2011.18

Filename

6103532