Volume 8 Number 9 ( Sep. 2013)
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JSW 2013 Vol.8(9): 2329-2335 ISSN: 1796-217X
doi: 10.4304/jsw.8.9.2329-2335

Research on Image Semantic Information Mining Based On Latent Dirichlet Allocation Model

Sa Yang
Guangdong University of Education, Guangdong, Guangzhou 510303, China

Abstract—Focusing on the issues of lacking of semantic description on image identification and methods of mapping from low-level semantics to high-level semantics, this paper describes the experiments of identification of image semantic information by using LDA model, which can achieve the mapping from image visual feature to high-level semantics, and experiments on the data sets of Corel 5k and Corel 30k. The experiments test and verify that LDA model performs a good stability on identification of image semantic information, and advantageous on dimension accuracy and recall rate, which provide a new solution and an embodiment of the identifying of image semantics intelligently and automatically.

Index Terms—Image semantic information, Image identification, Visual word bag, LDA model.

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Cite: Sa Yang, "Research on Image Semantic Information Mining Based On Latent Dirichlet Allocation Model," Journal of Software vol. 8, no. 9, pp. 2329-2335, 2013.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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