
Proceedings Paper
Effective image annotation based on the diverse density algorithm and keywords correlationFormat | Member Price | Non-Member Price |
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Paper Abstract
Automatic image annotation is significance for image understanding and retrieve of web image, so it becomes the new
hot research topic in recent years. This paper proposes an effective annotation method based on the Diverse Density
(DD) algorithm and keywords correction. The method includes two sub-processes, basic image annotation and
annotation refinement. In the basic label process, we use the improved DD algorithm to find the visual feature vector for
some semantic concept. The general DD algorithm uses all instances in the positive bags as start points of the
optimization process, which will greatly increase the computing time. We cluster the same visual feature regions in the
positive bags and use the clustering centers as start points instead of all instances. Moreover, the negative instances have
been used to guild the selection of start point. Then, we integrate the improved DD algorithm into the Bayesian
framework to realize the initial image annotation. In the annotation refinement, the correlations between keywords are
added to refine those candidate annotations from the prior process. Finally, experimental results and comparisons on the
Corel image set are given to illustrate the performance of the new algorithm.
Paper Details
Date Published: 8 July 2011
PDF: 6 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80091L (8 July 2011); doi: 10.1117/12.896094
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
PDF: 6 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80091L (8 July 2011); doi: 10.1117/12.896094
Show Author Affiliations
Keping Wang, Henan Polytechnic Univ. (China)
Zhigang Zhang, Jiaozuo Univ. (China)
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
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