DocumentCode :
1940360
Title :
Semantic Classification of Web Images for Efficient Image Retrieval
Author :
Jayaratne, Lakshman ; Ginige, Athula ; Jiang, Zhuhan
Author_Institution :
Sch. of Comput. & Inf. Technol., Univ. of Western Sydney, NSW
Volume :
1
fYear :
2005
fDate :
28-30 Nov. 2005
Firstpage :
464
Lastpage :
470
Abstract :
Grouping images into semantically meaningful categories using basic low-level visual features is a challenging and important problem in content-based image retrieval. The enormity and diversity of the visual contents on the Web images adds another dimension to this challenging task. Moreover, the retrieval of Web images cannot be easily achieved with images of other than trivial collections, and therefore one needs to put more cognitive load on the users. Based on the groupings, effective indices can however be built for an image database. In this paper, we show how a specific high-level classification problem can be solved from relatively basic low-level visual features geared for the particular classes. We have developed a procedure to qualitatively measure the saliency of a feature towards a classification problem based on the discrimination power of the HSV color histograms, which capture the visual characteristics of each of the images were computed. We found that the HSV color histogram, mainly the hue component, has the most discriminative power for the classification problem of our interest. A k-means classifier is used for the classification, which results in an accuracy of 90.5% when evaluated on an image database of 2,738 Web images. The images are classified as full faces, natural sceneries, events and city images. Our final goal is to use this classification knowledge to enhance the performance of content-based image retrievals by filtering out images from irrelevant classes during the matching
Keywords :
content-based retrieval; image classification; image colour analysis; image matching; image retrieval; semantic Web; visual databases; HSV color histogram; Web image; content-based image retrieval; image database; image matching; semantic classification; Content based retrieval; Digital images; Histograms; Image databases; Image retrieval; Information retrieval; Multimedia databases; Spatial databases; Visual databases; World Wide Web;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Modelling, Control and Automation, 2005 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-7695-2504-0
Type :
conf
DOI :
10.1109/CIMCA.2005.1631308
Filename :
1631308
Link To Document :
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