A Search-Based Web Image Annotation Method

Abstract

Automatic image annotation is an effective way for managing and retrieving abundant images on the internet. In this paper, we propose a novel search-based method for web image annotation. Firstly, surrounding text and other textual information in the hosting web pages are used as the candidate annotations. As the candidates are very noisy, two measures are defined to re-rank them and only top-ranked ones are reserved as the final annotations. One measure is based on the visual consistence between the given image and the image search results when the candidate annotation is submitted as a query. The other measure is based on the textual consistence between one candidate and others, which is calculated from the pairwise co-occurrence using image search engines. Finally, Dempster-Shafer multiple evidence combination approach is used to combine the visual and textual measures for the final ranking. Experimental results on web images demonstrate the effectiveness of the proposed method.