DocumentCode :
721081
Title :
Fusion of Dominant Colour and Spatial Layout Features for Effective Image Retrieval of Coloured Logos and Trademarks
Author :
Yijun Yan ; Jinchang Ren ; Yinsheng Li ; Windmill, James ; Ijomah, Winifred
Author_Institution :
Dept. of Electron. & Electr. Eng., Univ. of Strathclyde, Glasgow, UK
fYear :
2015
fDate :
20-22 April 2015
Firstpage :
306
Lastpage :
311
Abstract :
Due to its uniqueness and high value in commercial side, logos and trademarks play a key role in e-business based global marketing. Detecting misused and faked logos need designated and accurate image processing and retrieval techniques. However, existing colour and shape based retrieval techniques, which are mainly designed for natural images, cannot provide effective retrieval of logo images. In this paper, an effective approach is proposed for content-based image retrieval of coloured logos and trademarks. By extracting the dominant colour from colour quantization and measuring the spatial similarity, fusion of colour and spatial layout features is achieved. The proposed approach has been tested on a database containing over 250 logo images. Experimental results show that the proposed methodology yields more accurate results in retrieving relevant images than conventional approaches even with added Gaussian and Salt & pepper noise.
Keywords :
Gaussian noise; content-based retrieval; image colour analysis; image fusion; image retrieval; quantisation (signal); Gaussian noise; colour quantization; coloured logos; coloured trademarks; content-based image retrieval; dominant colour features; feature fusion; salt&pepper noise; spatial layout features; Colored noise; Feature extraction; Image color analysis; Image retrieval; Quantization (signal); Trademarks; Image retrieval; dominant colour descriptor; logo and trademark retrieval; spatial layout;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Multimedia Big Data (BigMM), 2015 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4799-8687-3
Type :
conf
DOI :
10.1109/BigMM.2015.43
Filename :
7153905
Link To Document :
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