期刊文献+

基于内容的大规模图像检索基本方法

下载PDF
导出
摘要 基于内容的图像检索方法是利用互联网上大量的图像信息,以计算机视觉、信息检索、统计学习等理论为基础,发展图像内容的提取和检索技术。本文主要针对提取的显著点和特征缺乏语义信息的问题,提出将显著点和SVM相关反馈结合的图像检索方法。
作者 徐磊
出处 《科技信息》 2013年第8期305-305,306,共2页 Science & Technology Information
  • 相关文献

参考文献5

二级参考文献37

  • 1[1]Rui Y, Huang T S, Ortega M, et al. Relevance feedback: A power tool for interactive content-based image retrieval. IEEE Trans on Circuits and Video Technology, 1998,8(5)
  • 2[2]Cox I, Miller M, Omohundro S M,et al. Pichunter: Bayesian relevance feedback for image retrieval system. In: Int'l Confon Pattern Recognition. Vienna, Austria, 1996.361~369
  • 3[3]Vasconcelos, Lippman A. Bayesian representations and learning mechanisms for content based image retrieval. In: SPIE Storage and Retrieval for Media Databases. San Jose, CA, 2000
  • 4[4]Rui Y,Huang T S. A Novel Relevance Feedback Technique in Image Retrieval. ACM Multimedia, 1999
  • 5[5]Su Zhong,Zhang Hongjiang. Using Bayesian Classifier in Relevant Feedback of Image Retrieval
  • 6[6]Qian Fang,Li Mingjing, Zhang Lei. Gaussian Mixture model for relevance feedback in image retrieval
  • 7[7]Lee C,Ma W Y, Zhang H J. Information Embedding Based on User's relevance Feedback for Image Retrieval: [ Technical Report HP Laps]. 1998
  • 8[8]Wood M E J, Campbell N W, Thomas B T. Iterative refinement by relevance feedback in content-based digital image retrieval. In:Proc. of the 6th ACM Int'l Conf on Multimedia'98. Bristol, England, 1998
  • 9[10]Flickner M, et al. Query by Imageand video content: the QBIC system. IEEE Computer, 1995,28(9) :23~32
  • 10[11]Pentland A, Picard R, Sclaroff S. Photobook: Content-based manipulation of image databases. International Journal of Computer Vision,1996,18(3): 233~254

共引文献48

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部