期刊文献+

基于Contourlet变换的加权小波特征抽取算法 被引量:3

Weighted Wavelet Feature Extraction Algorithm Based on Contourlet Transform
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摘要 特征提取是模式识别中的一个关键问题。本文提出了一种基于Contourlet变换的特征抽取算法。Con-tourlet变换具有多方向性和各向异性,能以接近最优的方式描述图像的边缘和纹理。文中算法利用Contourlet变换各子带系数的统计特性,构造特征矢量。Contourlet变换获得的特征是图像的局部特征,图像不同子带特征的分类能力是不相同的,针对各子带数据的离散程度进行加权处理,为分类能力强的特征量赋予较大的权值。该算法充分利用样本的统计信息,简捷、高效,并具有一定的鲁棒性。将该算法应用于Brodatz图像库纹理图像的检索,验证了算法的有效性。 Feature extraction is one of the key problems in pattern recognition system. A feature extraction algorithm is proposed based on the Contourlet transform. Contourlet transform can be used to effectively describe image edges and textures in both the location and the direction. The extracted feature vector has advantage of the statistical attribution of Contourlet transform coefficients. Local characters can be obtained with Contourlet transform and they have different discrimination qualities. The feature vector is weighted according to their degrees of the dispersion, and the feature with higher discrimination quality has bigger weight. The algorithm is used to texture retrieval and the promising results is obtained. In the retrieval experiments, a subset of the Brodatz image data is used. Finally, the experimental result shows improvements on the performance for various oriented textures.
出处 《数据采集与处理》 CSCD 北大核心 2008年第1期23-26,共4页 Journal of Data Acquisition and Processing
基金 国内科技合作和长三角联合攻关(2005E60007)资助项目 江苏省“六大人才高峰”(07-E-024)资助项目
关键词 CONTOURLET变换 特征提取 广义高斯分布 Contourlet transform feature extractions generalized Gaussian distribution
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参考文献5

  • 1Do M N, Vetterli M. The Contourlet transform: an efficient directional multiresolution image representation [J]. IEEE Transaction on Image Processing, 2005, 14(12): 2091 2106.
  • 2Do M N, Vetterli M. Framing pyramids [J]. IEEE Transaction on Signal Processing, 2003, 51 (9): 2329-2342.
  • 3Po D D Y, Do M N. Directional multiscale modeling of images using the Contourlet transform [J]. IEEE Transactions on Image Processing, 2006, 15 (6): 1610 1620.
  • 4Do M N, Vetterli M. Wavelet-based texture retrieval using generalized Gaussian density and Kullback-Leibler distance [J]. IEEE Transactions on Image Processing, 2002,11(3) : 146-158.
  • 5Manjunath B S, Ma W Y. Texture features for browsing and retrieval of image data [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996,18(8) :837-842.

同被引文献21

  • 1范立南,徐心和.基于不变矩特征和神经网络的图像模式模糊分类[J].东北大学学报(自然科学版),2004,25(8):738-741. 被引量:12
  • 2潘泓,夏良正.基于多尺度分析的小波不变矩[J].电路与系统学报,2006,11(1):55-59. 被引量:4
  • 3杨明,刘强,尹忠科,王建英.基于轮廓追踪的字符识别特征提取[J].计算机工程与应用,2007,43(20):207-209. 被引量:7
  • 4Xiaozhou H. Image recognition based on wavelet invar- iant moments and wavelet neural network[C]//Inter- national Conference on Information Acquisition, Seog- wipo: IEEE, 2007 : 275-279.
  • 5Po DDY, Do M N. Directional multiscale modeling of images using the contourlet transform[J]. Image Pro- cessing, IEEE Transactions on, 2006, 15 (6) : 1610- 1620.
  • 6Sing J K. Self-adaptive RBF neural network-based seg- mentation of medical images of the brain[J]. Intelli-gent Sensing and Information Processing, 2005: 447- 452.
  • 7ZHANG D S, LUG J. Review of shape representation and description techniques [ J ]. Pattern Recognition,2004 ( 37 ) : 1-19.
  • 8MA F,CHANG C Q,HUNG Y S. A subsapce approach for matching 2D shapes under affine distortions [ J ]. Pattern Recognition, 2011 (44) : 210-221.
  • 9ZHANG H, SHU H Z, HAIGRON P, et al. Construction of a complete set of orthogonal fourier-mellin moment invariants for pattern recognition ap- plications[J]. Image and Vision Computing,2010(28):38-44.
  • 10ZHANG F,LIU S Q, WANG D B, et al. Aircraft recognition in infrared image using wavelet moment invariants [ J]. Image and Vision Compu- ting,2009(27) :313-318.

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