期刊文献+

一种基于灰度共生矩阵的文本图像识别方法 被引量:11

Approach for Document Image Recognizing Based on Grey Co-occurrence Matrix
下载PDF
导出
摘要 提出了一种有效的文本图像识别方法。在对文本图像与非文本图像纹理特征差异进行分析的基础上,计算了一种新的图像灰度共生矩阵统计量,进而据此对图像属性作出判决。实验结果表明了该方法的有效性。 This paper presents an effective method for recognizing document images. Based on the analysis of the difference between the texture of document images and that of non-document images, the new method computes a new co-occurrence statistic, after which the decision is made hereby. Experimental result proves its validity.
作者 庄军 李弼程
出处 《计算机工程》 CAS CSCD 北大核心 2006年第3期214-216,共3页 Computer Engineering
关键词 共生矩阵 文本图像 图像识别 纹理特征 Co-occurrence matrix Document image hnage recognize Texture feature
  • 相关文献

参考文献5

二级参考文献24

  • 1王润生.图像理解[M].长沙:国防科技大学出版社,1994..
  • 2孙即祥.数字图像处理[M].石家庄:河北教育出版社,1991..
  • 3章毓晋 刘忠伟.基于HSI模糊和累积直方图的彩色图像检索.第八届全国信号处理学组委员会联合会议论文集[M].,1997.256-260.
  • 4[1]Smeulders A W M, Worring M, Santin S i, Gupta A, and Jain R. Content-based image retrieval at the end of the early years[J]. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2000-12, 22(12):1349-1380..
  • 5[2]Remco C, et al.. Content -Based Image Retrieval Systems: A Survey[D]. Department of Computing Science, Utrecht University, 2000-10.
  • 6[3]Flickner M et al. The QBIC project: Querying images by content using color, texture and shape[A]. In: SPIE Storage and Retrieval of Image and Video Databases[C], (1993).
  • 7[4]Pentland A, Picard R and Sclaroff S. Photobook: Content-based Manipulation of Image Databases[A]. In SPIE Storage and Retrieval for Image and Video Databases II[C], number 2185, 1994-02.
  • 8[5]Kelly P M and Cannon T M. CANDID: Comparison algorithm for navigating digital image databases[A]. Proceedings of the Seventh International Working Conference on Scientific and Statistical Database Management[C], 1994-09, 252-258.
  • 9[6]Yong Rui, Thomas S Huang, Chang Shih-Fu. Image retrieval: past, present, and future[J]. Journal of Visual Communication and Image Representation, 1998.
  • 10[7]Minka T. An image database browser that learns from user inter-action[R]. M.I.T. Media Lab. Perceptual Computing Section, TR 365, 1996

共引文献90

同被引文献92

引证文献11

二级引证文献73

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