Title
Integrated color, texture and shape information for content-based image retrieval
Abstract
Feature extraction and the use of the features as query terms are crucial problems in content-based image retrieval (CBIR) systems. The main focus in this paper is on integrated color, texture and shape extraction methods for CBIR. We have developed original CBIR methodology that uses Gabor filtration for determining the number of regions of interest (ROIs), in which fast and effective feature extraction is performed. In the ROIs extracted, texture features based on thresholded Gabor features, color features based on histograms, color moments in YUV space, and shape features based on Zernike moments are then calculated. The features presented proved to be efficient in determining similarity between images. Our system was tested on postage stamp images and Corel photo libraries and can be used in CBIR applications such as postal services.
Year
DOI
Venue
2007
10.1007/s10044-007-0071-0
Pattern Anal. Appl.
Keywords
DocType
Volume
shape information,color moment,feature extraction,original cbir methodology,shape extraction method,thresholded gabor feature,content-based image retrieval,integrated color,corel photo library,effective feature extraction,gabor filtration,cbir application,computer vision,image retrieval,region of interest
Journal
10
Issue
ISSN
Citations 
4
1433-755X
13
PageRank 
References 
Authors
0.63
22
3
Name
Order
Citations
PageRank
Ryszard S. Choras1376.72
Tomasz Andrysiak2349.35
Michał Choraś312918.82