A combination of graph ranking and term collocation information for image annotation
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2006
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eng
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39 leaves
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b152591
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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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National Institute of Development Administration. Library and Information Center
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Krittapad Suriya (2006). A combination of graph ranking and term collocation information for image annotation. Retrieved from: http://repository.nida.ac.th/handle/662723737/415.
Title
A combination of graph ranking and term collocation information for image annotation
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Abstract
In a large image database, an automatic image annotation plays an important
role to assign a caption to an image. There are many applications of image annotation
which include information extraction, knowledge acquisition, finding answers from
specific questions, etc.
In this research, we propose an image annotation approach using a graph
ranking algorithm on a novel structure which includes similarities among regions
within images and caption term collocation information. Caption terms are selected
using a graph random walk method biased toward the query image. A series of
experiments are performed on standard image data sets to evaluate the proposed
approach. The results show the annotation accuracy of 56.96%.
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Thesis (M.S. (Computer Sience))--National Institute of Development Administration, 2006.