A Strategy of Semantic Information Eztraction for Web Image
In order to improve semantic information extraction coverage and quality of Web images, A novel approach is presented in this paper. Based on the habit of users to retrieve images, the model of representing image semantics is put forward. According to the model, a series of dictionaries are built, which include image topic, object and attribute dictionaries. Eight kinds of text are extracted as image semantic source from Web pages. Combining with semantic dictionaries, image semantic keywords can be extracted from the eight kinds of text. The strategy of extracting image semantics is better than existing technique, which is better than manual annotation in efficiency and better than automatic annotation based on content in accuracy. A performance experiment is presented which shows that high extraction coverage and quality can be achieved with this approach. The similar approaches could be applied to extract semantic information of other forms of multimedia.
Web images semantic dictionary information eztraction image annotation image retrieval
Wenpeng Lu Haixia Li Ruojuan Xue Jianguo Wang
Department of Information Science and Technology Shandong Institute of Light Industry Jinan, 250353, Department of Information Technology Shandong Youth College Jinan, 250014, China LiShan School Shandong Normal University Jinan, 250014, China Department of Information Science and Technology Taishan College Taian, 271000, China
国际会议
北京
英文
480-483
2009-07-24（万方平台首次上网日期，不代表论文的发表时间）