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基于图像能量谱直方图的纹理检索算法RAH 被引量：3

RAH: A Texture Based Image Retrieval Algorithm Based on the Histogram of Image Power Spectral
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摘要 本文提出的基于纹理的图像检索算法RAH是以图像的能量谱直方图为基础,包括以下两个方面:第一,计算图像能量谱的半径和角度直方图的方法以及基于图像能量直方图的频率去提取纹理特征的算法;第二,基于纹理特征的相似度检测方程。这个实验结果表明,RAH算法优于一般的灰度共生矩阵纹理检索算法,具有较好的检索效果,比较适用于基于内容的图像检索。 A texture based image retrieval algorithm RAH based on the histogram of image power spectral in frequen- cy domain is proposed, which mainly includes the next two parts: first, the method of computing radius histogram and angular histogram and the algorithm of texture feature extraction based on the histogram of image power spectral in frequency domain, second, the similarity measurement function based on the texture feature. The experimental re- sults indicate that RAH is preferable to the traditional co-occurrence matrix based algorithm.
作者 丁玲 王崇俊 杨育彬 陈世福
机构地区 南京大学计算机软件新技术国家重点实验室
出处 《计算机科学》 CSCD 北大核心 2005年第1期194-197,201,共5页 Computer Science
基金 江苏省应用基础基金BJ20009
关键词 图像能量谱直方图 纹理 图像检索算法 RAH 灰度共生矩阵 相似度检测方程 Content-based image retrieval Texture feature extraction Co-occurrence matrix Similarity measurement function
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献6

  • 1Chang T. Kuo J. Texture analysis and classification with treestructured wavelet transform. IEEE Transactions on Image Processing, 1993,2(2) :429～441
  • 2Ma W Y, Manjunath B S. Texture features and learning similarity. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, 1996. 425～ 430
  • 3Jain A K, Farrokhnia F. Unsupervised texture segmentation using Gabor filters. Pattern Recognition, 1991,24:1167～1186
  • 4Wang J Z, Wiederhold G, Firschein O, Sha X W. Content-based image indexing and searching using Daubechies' wavelets. International Journal of Digital Libraries, 1998,1 (4): 311 ～ 328
  • 5Ma W Y, Zhang H J. Benchmarking of image features for content-based retrieval. In: Proc. 32nd Asilomar Conf. on Signals,Systems and Computers, California, US, Jan. 1998. 253～257
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同被引文献23

  • 1马晓凯,黎绍发.利用小波变换和纹理特征实现运动对象检测[J].计算机应用,2007,27(1):237-239. 被引量：2
  • 2Juan Chung-Wei,Hu Jwu-Shong.A new spatial-color mean-shift object tracking algorithm with scale and orientation estimation[C].IEEE International Conference on Robotics and Automation,2008:2265-2270.
  • 3Wang Junqiu,Yagi Yasushi.Integrating color and shapo-texture features for adaptive real-time object tracking[J].IEEE Transactions on Image Processing,2008,17(2):235-240.
  • 4Christian Gosch,Ketut Fundana,mAnders Heyden,et al.View point tracking of rigid objects based on shape sub-manifolds[J].Europenn Conference on Computer Vision,2008(3):251-263.
  • 5Chang Huang,Bo Wu,Ramakant Nevatia.Robust object tracking by hierarchical association of detection responses[J].European Conference on Computer Vision,2008(2):788-801.
  • 6Liu Xiuwen,Wang Deliang.Image and textures segmentation using local spectral histograms[J].IEEE Transactions on Image Processing,2006,15(10):3066-3077.
  • 7Wang Junqiu,Yasushi Yagi.Integrating Color and Shape-Texture Features for Adaptive Real-Time Object Tracking[J].IEEE Transactions on processing Image,2008,17(2):235-240.
  • 8Juan Chung-wei,HuJwu-sheng.A New Spatial-Color Mean-Shift Object Tracking Algorithm with Scale and Orientation Estimation[J].2008 IEEE International Conference on Robotics and Automation,2008.2265-2270.
  • 9Liu Xiuwen,Wang Deliang.Image and textures segmentation using local spectral histograms[J].IEEE transactions on image processing,2006,15(10):3066-3077.
  • 10Niblack W, Barber R. The QBIC project: querying images by content using color, texture and shape[M]. In.. San Jose , California ,SHE, 1993. 173-187

引证文献3

二级引证文献19

计算机科学
2005年 第1期

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