计算机工程与应用 ›› 2009, Vol. 45 ›› Issue (16): 176-179.DOI: 10.3778/j.issn.1002-8331.2009.16.051
• 图形、图像、模式识别 • 上一篇 下一篇
张文娇,闫德勤,桑 雨
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ZHANG Wen-jiao,YAN De-qin,SANG Yu
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摘要： 研究基于支持向量机和粗糙集的相关反馈图像检索算法。利用粗糙集理论，通过对训练集的学习，构造分类规则，对支持向量机反馈后的结果再次进行处理。实验显示，与现有方法相比，该方法在图像检索的性能和时间上都有明显的改善。
关键词: 图像检索, 相关反馈, 支持向量机, 粗糙集
Abstract: Relevance feedback algorithm based on support vector machine and rough set for image retrieval is approached.By using rough set theory，this paper structures classification rules and processes the support vector machine feedback results with learning the train set.Experiments show that compared with the existing methods，the new algorithm can significantly improve the quality of the retrieval performance and save time.
Key words: image retrieval, relevance feedback, support vector machine, rough set
张文娇,闫德勤,桑 雨. 基于支持向量机和粗糙集的图像检索算法[J]. 计算机工程与应用, 2009, 45(16): 176-179.
ZHANG Wen-jiao,YAN De-qin,SANG Yu. Image retrieval algorithm based on support vector machine and rough set theory[J]. Computer Engineering and Applications, 2009, 45(16): 176-179.
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链接本文: http://cea.ceaj.org/CN/10.3778/j.issn.1002-8331.2009.16.051
http://cea.ceaj.org/CN/Y2009/V45/I16/176
