The full text of this article


Ranking images in web documents based on HTML TAGs for image retrieval from WWW
by P. Shanmuga Vadivu; P. Sumathy; A. Vadivel
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 3, No. 2/3, 2014


Abstract: Large number of images are embedded into web pages and it is difficult to map the semantics of the images using available text in documents. Retrieval systems are designed for ranking and retrieving images using various ranking mechanisms. These ranking mechanisms use the text present in the HTML document and this alone may not be sufficient for improving precision of retrieval. In this paper, the text present in the <IMG> TAG is analysed and each attribute in the TAG is categorised into four levels. A suitable weight is assigned to the attribute values of different levels such that the importance of each level is considered. The top level attributes are assigned higher weights and lower weight is assigned to the lowest level attributes. We have compared the performance with the Google image search system and observed that the performance of the proposed approach is encouraging.

Online publication date: Wed, 11-Jun-2014


is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Intelligence Studies (IJCISTUDIES):
Login with your Inderscience username and password:


    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email