Paper Title:
An Efficient Web Image Annotation Ranking Algorithm
  Abstract

Existing image annotation approaches mainly concentrate on achieving annotation results. Annotation order has not been taken into account carefully. As orderly annotation list could enhance the performance of image retrieval system, it is of great importance to rank annotations. This paper presents an algorithm to rank Web image annotating results. For an annotated Web image, we firstly partition the image by a region growing method. Secondly, relevance degree between two annotations is estimated through considering both semantic similarity and image content. Next, the regions of unlabeled image to be ranked serve as queries and annotations are used as the data points to be ranked. And then, manifold-ranking algorithm is executed to get the ordered annotation list. Experiments conducted on real-world Web images through NDCG metric demonstrate the effectiveness of the proposed approach.

  Info
Periodical
Advanced Materials Research (Volumes 108-111)
Edited by
Yanwen Wu
Pages
81-87
DOI
10.4028/www.scientific.net/AMR.108-111.81
Citation
Z. Liu, "An Efficient Web Image Annotation Ranking Algorithm", Advanced Materials Research, Vols. 108-111, pp. 81-87, 2010
Online since
May 2010
Authors
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Price
$32.00
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