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An Efficient Algorithm to Reduce the Semantic Gap between Image Contents and Tags
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 72 - Number 11 |
| Year of Publication: 2013 |
| Authors: Grishma Y. Bobhate, Usha A. Jogalekar |
10.5120/12541-9136
|
Grishma Y. Bobhate, Usha A. Jogalekar . An Efficient Algorithm to Reduce the Semantic Gap between Image Contents and Tags. International Journal of Computer Applications. 72, 11 ( June 2013), 38-44. DOI=10.5120/12541-9136
Abstract
With the rapid growth in the new era of Internet Technology, image retrieval is an active and traditional method for searching the images by keywords or by images from the large amount of image database. As tags gives the descriptive information of an image on the web. Due to noisy nature in tags, it becomes necessary to correlate both image content and tag information for retrieval purposes. However, semantic gap is a major problem in the image processing concept. Therefore, our presented research is going to reduce the problem of semantic gap by applying techniques to extract low level features of an image such as color, texture and edge. Then, construction of a mixed graph between image and tag to perform random walk on graph for getting accurate results in an efficient way. Experimental results show the effectiveness of our approach.
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