Soo-Sun Cho, Journal of Internet Computing and Services, Vol. 11, No. 3, pp. 15-24, Jun. 2010
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Keywords: Web image classification, semantically related tags, content based classification, Flickr, bag of visual word, PLSA

Abstract

In this paper, we propose an image classification which combines semantic relations of tags with contents of images to improve the satisfaction of image retrieval on application domains as huge image sharing sites. To make good use of image retrieval or classification algorithms on huge image sharing sites as Flickr, they are applicable to real tagged Web images. To classify the Web images by 'bag of visual word' based image content, our algorithm includes training the category model by utilizing the preliminary retrieved images with semantically related tags as training data and classifying the test images based on PLSA. In the experimental results on the Flickr Web images, the proposed method produced the better precision and recall rates than those from the existing method using tag information.

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