DocumentCode :
1905784
Title :
Content-based image retrieval system based on combined and weighted multi-features
Author :
Bounthanh, Machine ; Hamamoto, Kiichi ; Attachoo, Boonwat ; Bounthanh, Tha
Author_Institution :
Int. Coll., King Mongkut´s Inst. of Technol. Ladkrabang, Bangkok, Thailand
fYear :
2013
fDate :
4-6 Sept. 2013
Firstpage :
449
Lastpage :
453
Abstract :
This paper, we proposed a novel framework for combining and weighting all of three i.e. color, shape and texture features to achieve higher retrieval efficiency. The color feature is extracted by quantifying the YUV color space and the color attributes like the mean value, the standard deviation, and the image bitmap of YUV color space is represented. The texture features are obtained by the entropy based on the gray level cooccurrence matrix and the edge histogram descriptor of an image. The shape feature descriptor is derived from Fourier descriptors (FDs) and the FDs derived from different signatures. When computing the similarity between the query image and target image in the database, normalization information distance is also used for adjusting distance values into the same level. And then the linear combination has used to combine the normalized distance of the color, shape and texture features to obtain the similarity as the indexing of image. Furthermore, an experimental results indicated, a weight variation to achieve higher retrieval efficiency and the proposed technique indeed outperforms other schemes in terms of the accuracy and efficiency.
Keywords :
content-based retrieval; feature extraction; image colour analysis; image retrieval; image texture; Fourier descriptors; YUV color space; color attributes; color features; content-based image retrieval system; edge histogram descriptor; entropy; gray level cooccurrence matrix; linear combination; normalization information distance; query image; retrieval efficiency; shape features; texture features; weight variation; Feature extraction; Histograms; Image color analysis; Image edge detection; Image retrieval; Shape; Color distribution; Content-based image retrieval (CBIR); Fourier descriptors; Gray level co-occurrence matrix; Image bitmap; YUV;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications and Information Technologies (ISCIT), 2013 13th International Symposium on
Conference_Location :
Surat Thani
Print_ISBN :
978-1-4673-5578-0
Type :
conf
DOI :
10.1109/ISCIT.2013.6645900
Filename :
6645900
Link To Document :
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