DocumentCode :
3272451
Title :
Image pre-classification based on saliency map for image retrieval
Author :
Liang, Zhen ; Fu, Hong ; Chi, Zheru ; Feng, Dagan
Author_Institution :
Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., Hong Kong, China
fYear :
2009
fDate :
8-10 Dec. 2009
Firstpage :
1
Lastpage :
5
Abstract :
In content-based image retrieval, it is helpful to add a pre-classification module to classify a query image into attentive class or non-attentive class. Based on the pre-classification result, a suitable retrieval strategy is adopted for the query image presented. In this paper, we proposed a Multi-Layer Perceptron (MLP) classifier with the features extracted from saliency map to classify both the query image and database images into attentive images and non-attentive classed. A dataset of 1,000 images was selected from the 7,346 Hemera color image database for our experiments. Various features extracted from the saliency map are investigated, including the number and the average size of saliency regions, the variance of the sizes of saliency regions, as well as the sizes of the three most conspicuous saliency regions. The number and average size of saliency regions in the saliency map are shown to be the most discriminative features with which a classification rate of better than 98% can be achieved. To facilitate multi-strategy image retrieval, we define an attentive index between 0 and 1 based on the two most discriminative features to indicate how attentive an image is. Finally, two image retrieval strategies based on the attentive index are proposed, and the corresponding image retrieval performances are evaluated on the 7,346 Hemera color image database with a comparison with the other conventional image retrieval methods.
Keywords :
content-based retrieval; feature extraction; image classification; image retrieval; multilayer perceptrons; query formulation; visual databases; attentive images; attentive index; content-based image retrieval; database image classification; features extraction; image preclassification module; multilayer perceptron classifier; nonattentive images; query image classification; saliency map; Color; Content based retrieval; Feature extraction; Image databases; Image retrieval; Indexes; Information retrieval; Multilayer perceptrons; Performance evaluation; Spatial databases; Image classfication; attentive index; attentive objects; image retrieval; non-attentive objects; saliency map;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information, Communications and Signal Processing, 2009. ICICS 2009. 7th International Conference on
Conference_Location :
Macau
Print_ISBN :
978-1-4244-4656-8
Electronic_ISBN :
978-1-4244-4657-5
Type :
conf
DOI :
10.1109/ICICS.2009.5397714
Filename :
5397714
Link To Document :
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