期刊文献+

基于HSV颜色空间加权Hu不变矩的台标识别 被引量:11

TV Symbol Recognition Based on Weighted Hu Invariant Moments in HSV Colour Space
下载PDF
导出
摘要 该文根据台标的视觉特征,提出基于时空不变区域检测的方法来进行台标分割,并对台标特征提出用基于HSV颜色空间的加权Hu不变矩进行描述,最后采用基于知识库的方法进行台标识别。实验表明:该算法识别正确率较高,效果基本令人满意。 According to the visual features of a TV station symbol, TV station symbol is segmented by the detection of spatio-temporal invariant region. The features of a TV station symbol are described with weighted Hu invariant moments in HSV color space and recognized on the basis of knowledge base. The algorithm is experimentally satisfying.
出处 《南京理工大学学报》 EI CAS CSCD 北大核心 2005年第3期363-367,共5页 Journal of Nanjing University of Science and Technology
关键词 视频检索 台标识别 加权Hu不变矩 时空不变性 video retrieval TV station symbol recognition weighted Hu invariant moments spatio-temporal invariant
  • 相关文献

参考文献13

  • 1Yeo B L, Yeung M M.Retrieving and visualizing video [J].ACM Communication.1997,40(12): 47-52.
  • 2Chang S F, Chen W, Sundaram H.VideoQ: An automated content based video search system using visual cues [A].Seattle: ACM Multimedia 1997, 1997: 313-324.
  • 3Wactlar H, Kanade T, Smith M.Intelligent access to digital video: informedia project [J].IEEE Computer, 1999, 29(6): 46-52.
  • 4詹国华,庄越挺,吴翌.基于全局与局部特征的视频索引模型[J].计算机辅助设计与图形学学报,2000,12(12):911-916. 被引量:7
  • 5Chan S M, Li Q, Wu Y.Accommodation hybrid retrieval in a comprehensive video database management system [J].IEEE Traction on multimedia, 2002, 4(2): 146-159.
  • 6庄越挺,刘骏伟,吴飞,潘云鹤,张引.基于支持向量机的视频字幕自动定位与提取[J].计算机辅助设计与图形学学报,2002,14(8):750-753. 被引量:38
  • 7吴飞,庄越挺,郑科,刘骏伟,潘云鹤.基于压缩域特征话者识别的电视节目分类检索[J].模式识别与人工智能,2002,15(1):21-27. 被引量:2
  • 8季白杨,陈纯,钱英.视频分割技术的发展[J].计算机研究与发展,2001,38(1):36-42. 被引量:36
  • 9A.NuratTekalp 崔之祐 江春 陈丽鑫译.数字视频处理[M].北京:电子工业出版社,1998..
  • 10章毓晋.图像处理和分析[M].北京:清华大学出版社,1999..

二级参考文献33

  • 1TEKALP A M 崔之枯等(译).数字视频处理[M].北京:电子工业出版社,1998..
  • 2[1]Y Wang, Z Liu, J Huang. Multimedia content analysis using audio and visual information[J]. IEEE Signal Processing Magazine, 2000, 17(6):12~36
  • 3[2]R Lienhart, F Stuber. Automatic text recognition in digital videos[A]. In: Proceedings of ACM Multimedia, Boston, 1996.11~20
  • 4[3]Zhong Yu, Zhang Hongjiang, Jain Anil K. Automatic caption localization in compressed video[J]. Pattern Analysis and Machine Intelligence, 2000, 22(4):385~392
  • 5[4]V Vapnik. The Nature of Statistical Learning Theory[M]. New York: Springer, 1995
  • 6[5]M Schmidt. Identifying speaker with support vector networks[A]. In: Proceedings of Interface'96, Sydney, 1996
  • 7[6]T Joachims. Text categorization with support vector machines: Learning with many relevant features[A]. In: Proceedings of the 10th European Conference on Machine Learning, Chemnitz, Germany, 1998.137~142
  • 8[7]Yuan Qi. Learning algorithms for video and audio processing: Independent component analysis and support vector machine based approaches[R].College Park: University of Maryland at College Park, LAMP-TR-056(CAR-TR-951), 2000
  • 9[8]Edgar Osuna, Robert Freund, Federico Girosi. Training support vector machines: An application to face detection[A]. In: Proceedings of Computer Vision and Pattern Recognition, Puerto Rico, 1997.130~136
  • 10[9]C J C Burges. A tutorial on support vector machines for pattern recognition[J]. Data Mining, and Knowledge Discovery, 1998, 2(2):121~167

共引文献420

同被引文献71

引证文献11

二级引证文献27

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