DocumentCode :
3254352
Title :
An Attention-Based Image Retrieval System
Author :
Ozyer, Gulsah Tumuklu ; Vural, Fatos Yarman
Author_Institution :
Dept. of Comput. Eng., Middle East Tech. Univ., Ankara, Turkey
Volume :
1
fYear :
2011
fDate :
18-21 Dec. 2011
Firstpage :
96
Lastpage :
99
Abstract :
In this study, a new Content Based Image Retrieval system, called Attention-Based Image Retrieval (ABIR) is proposed by using the Itti-Koch visual attention model. For this purpose, first the regions are extracted by using the saliency maps. Then, the attention values, obtained from the saliency maps are used to define a new similarity metric. Finally, this metric is used to retrieve the similar regions. The proposed approach extracts the region of interests without employing any segmentation method. The extra emphasis given to high attention values, provide a better matching criterion, compared to the classical Euclidean distance. The power of the proposed method is demonstrated by the experiments. It is observed that ABIR retrieves with higher precision performance compared to the state of the art object based retrieval methods, in images with cluttered background.
Keywords :
content-based retrieval; feature extraction; image matching; image retrieval; Itti-Koch visual attention model; attention value; attention-based image retrieval system; classical Euclidean distance; cluttered background image; content based image retrieval system; matching criterion; object based retrieval method; region extraction; saliency map; similar region retrieval; similarity metric; Computational modeling; Feature extraction; Image color analysis; Image retrieval; Image segmentation; Object recognition; Visualization; CBIR; Visual Attention;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications and Workshops (ICMLA), 2011 10th International Conference on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4577-2134-2
Type :
conf
DOI :
10.1109/ICMLA.2011.27
Filename :
6146950
Link To Document :
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