DocumentCode :
606200
Title :
Combined texture and shape features for content based image retrieval
Author :
Daisy, M. Mary Helta ; Selvi, S. Thamarai ; Mol, J. S. Ginu
Author_Institution :
Dept. of ECE, SXCCE, Chunkankadai, India
fYear :
2013
fDate :
20-21 March 2013
Firstpage :
912
Lastpage :
916
Abstract :
Image retrieval refers to extracting desired images from a large database. The retrieval may be of text based or content based. Here content based image retrieval (CBIR) is performed. CBIR is a long standing research topic in the field of multimedia. Here features such as texture & shape are analyzed. Gabor filter is used to extract texture features from images. Morphological closing operation combined with Gabor filter gives better retrieval accuracy. The parameters considered are scale and orientation. After applying Gabor filter on the image, texture features such as mean and standard deviations are calculated. This forms the feature vector. Shape feature is extracted by using Fourier Descriptor and the centroid distance. In order to improve the retrieval performance, combined texture and shape features are utilized, because many features provide more information than the single feature. The images are extracted based on their Euclidean distance. The performance is evaluated using precision-recall graph.
Keywords :
Fourier transforms; Gabor filters; content-based retrieval; feature extraction; image retrieval; statistical analysis; CBIR; Euclidean distance; Fourier descriptor; Gabor filter; centroid distance; content based image retrieval; feature extraction; feature vector; mean; morphological closing operation; precision-recall graph; retrieval accuracy; shape feature; standard deviation; texture feature; Databases; Electronic mail; Gabor filters; Fourier descriptor; Gabor filter; Texture;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits, Power and Computing Technologies (ICCPCT), 2013 International Conference on
Conference_Location :
Nagercoil
Print_ISBN :
978-1-4673-4921-5
Type :
conf
DOI :
10.1109/ICCPCT.2013.6528956
Filename :
6528956
Link To Document :
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