Multiple Features Image Fusion Based on Visual Dictionary

Abstract:

It has been heavy work that to find the related pictures form Internet without annotation. Therefore, the automatic image annotation was extremely important in image retrieval. The traditional method were translated image visual feature into keywords simply, but it ignored the image similarity problem between the low-level visual features and high-level semantic. That is image "gap" problem, so image annotation was very lower. This paper puts forward a classification of web based image content automatic tagging mixing technology, the first it will map visual feature of image to one or more rough images, then we will preprocess the web page text information, finally we select some keywords similarity as image annotation by using similar semantic processing module. So it realizes the image and text combining the automatic annotation and it achieve high precision of image annotation.

• Periodical: Advanced Materials Research (Volumes 889-890)
• Pages: 1111-1114
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.889-890.1111
• Online since: February 2014
• Authors: Yu Ting*
• Keywords: Clustering, Dempster-Shafer Evidence Theory, Multi-Feature Fusion, Visual Dictionary

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