DocumentCode
3111288
Title
Efficient image retrieval based on texture features
Author
Fazal-e-Malik ; Baharudin, Baharum
Author_Institution
Dept. of Comput. & Inf. Sci., Univ. Teknol. PETRONAS, Tronoh, Malaysia
fYear
2011
fDate
19-20 Sept. 2011
Firstpage
1
Lastpage
6
Abstract
A quick and accurate algorithm for content-based image retrieval (CBIR) is proposed in this paper. The retrieval of the similar images using proposed algorithm from the database is based on the statistical texture features. The basic idea is to convert the RGB color image into grayscale image to reduce the computation speed and increase efficiency. The grayscale image is divided into blocks of different sizes. The statistical texture features are extracted by using the probability distribution of intensity levels in all blocks. In the experiment, the efficiency of feature extraction and accuracy of the image retrieval are measured for different block size methods using the proposed algorithm. The Corel database was used for testing. As a result the proposed CBIR algorithm provided higher performance in terms of efficiency and accuracy.
Keywords
content-based retrieval; feature extraction; image colour analysis; image retrieval; image texture; CBIR algorithm; Corel database; RGB color image; computation speed; content-based image retrieval; grayscale image; intensity level; probability distribution; statistical texture feature extraction; Databases; Entropy; Feature extraction; Gray-scale; Image color analysis; Probability distribution; Vectors; content-based image retrieval (CBIR); intensity levels; statistical texture features;
fLanguage
English
Publisher
ieee
Conference_Titel
National Postgraduate Conference (NPC), 2011
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4577-1882-3
Type
conf
DOI
10.1109/NatPC.2011.6136308
Filename
6136308
Link To Document