Semantic Fusion of Image Annotation

Xiao Ying Wu; Yun Juan Liang; Li Li; Li Juan Ma

doi:10.4028/www.scientific.net/AMR.268-270.1386

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 268-270Semantic Fusion of Image Annotation

Semantic Fusion of Image Annotation

Abstract:

In this paper, improve the image annotation with semantic meaning, and name the new algorithm for semantic fusion of image annotation, that is a image is given to be labeled, use of training data set, the word set, and a collection of image area and other information to establish the probability model ,estimates the joint probability by word and given image areas.The probability value as the size, combined with keywords relevant table that integrates lexical semantics to extract keywords as the most representative image semantic annotation results. The algorithm can effectively use large-scale training data with rich annotation, so as to achieve better recall and precision than the existing automatic image annotation ,and validate the algorithm in the Corel data set.

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Periodical:

Advanced Materials Research (Volumes 268-270)

Pages:

1386-1389

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.268-270.1386

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Online since:

July 2011

Authors:

Xiao Ying Wu, Yun Juan Liang, Li Li, Li Juan Ma

Keywords:

Image Annotation, Keywords Relevant Table, Semantic Fusion

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References

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