计算机科学 ›› 2017, Vol. 44 ›› Issue (6): 274-277.doi: 10.11896/j.issn.1002-137X.2017.06.048

• 图形图像与模式识别 • 上一篇    下一篇

基于改进双树复小波和灰度-梯度共生矩阵的纹理图像检索算法

翟奥博,温显斌,张鑫   

  1. 计算机视觉与系统省部共建教育部重点实验室天津理工大学 天津300384智能计算及软件新技术天津市重点实验室天津理工大学 天津300384,计算机视觉与系统省部共建教育部重点实验室天津理工大学 天津300384智能计算及软件新技术天津市重点实验室天津理工大学 天津300384,计算机视觉与系统省部共建教育部重点实验室天津理工大学 天津300384智能计算及软件新技术天津市重点实验室天津理工大学 天津300384
  • 出版日期:2018-11-13 发布日期:2018-11-13
  • 基金资助:
    本文受国家自然科学基金项目(61472278)资助

Retrieval Algorithm for Texture Image Based on Improved Dual Tree Complex Wavelet Transform and Gray Gradient Co-occurrence Matrix

ZHAI Ao-bo, WEN Xian-bin and ZHANG Xin   

  • Online:2018-11-13 Published:2018-11-13

摘要: 针对双树复小波变换缺少不同尺度纹理的空间分布特征的缺陷,提出了一种改进双树复小波和灰度-梯度共生矩阵相融合的纹理图像检索新算法。首先,该算法将图像进行非均匀分块,并对分块的图像进行双树复小波变换,以此增加不同尺度下的空间信息;其次,利用灰度-梯度共生矩阵提取4个统计量特征;然后, 融合 两种方法提取的纹理特征以得到图像检索的纹理特征;最后,用Canberra距离进行相似性度量并输出图像检索的结果。实验结果表明,该方法对纹理图像有较好的检索效果。

关键词: 图像检索,双树复小波变换,灰度-梯度共生矩阵

Abstract: To overcome the lack of texture space distribution cha racteristics at different scales for dual tree complex wavelet transform,a kind of improved retrieval algorithm for texture image was proposed based on the combining dual tree complex wavelet transform with gray gradient co-occurrence matrix.Firstly,in order to increase the spatial information at different scales,the algorithm will be non-uniform image blocks,and every block image is dual tree complex wavelet transform.Secondly,the four statistical features are extracted by using gray gradient co-occurrence matrix.Then,texture features for image retrieval are obtained using fusion of texture feature extracted by above two methods.Finally,Canberra distance is used similarity measure and output image search results.Experimental results show that this method has better retrieval results for texture images.

Key words: Image retrieval,Dual tree complex wavelet transform,Gray gradient co-occurrence matrix

[1] LONG S J.Study on Extraction of image texture feature in ima-ge retrieval [M].Chengdu:Southwest Jiao Tong University,2012:1-3.(in Chinese) 龙士军.图像检索中纹理特征提取的研究[M].成都:西南交通大学,2012:1-3.
[2] XU Y F,GONG X Y,GONG S F.An algorithm for texture-based Image Retrieval[C]∥2011 International Conference on Communication,Networking and Broadcasting.2011,6:145-147.
[3] YUE L.Image retrieval based on block color moment and gray level co-occurrence matrix[J].Micro Computer Information,2012,8(28):162-164.(in Chinese) 岳磊.基于分块颜色矩和灰度共生矩阵的图像检索[J].微计算机信息,2012,8(28):162-164.
[4] QI Y L.A Relevance Feedback Retrieval Method Based on Ta-mura Texture[J].Second International Symposium on Know-ledge Acquisition and Modeling,2009,2(3):174-177.
[5] LAM S W C.Texture feature extraction using gray level gradie-nt based co-occurrence matrices[J].IEEE International Confe-rence on Systems,Man and Cybernetics,1996(1):267-271.
[6] LIU L W,CHEN X W,YING Z W.Texture image retrieval algorithm with dual tree complex contourlet and three statistical features[C]∥IEEE 3rd International Conference on Communication Software and Networks(ICCSN).2011,5:349-352.
[7] HUANG Y Y,ZHANG Y S.Dual tree complex wavelet domain co-occurrence matrix texture extraction method[J].Computer Applications and Software,2012,7(29):216-219.(in Chinese) 黄媛媛,张尤赛.双树复小波域共生矩阵的纹理提取方法[J].计算机应用与软件,2012,7(29):216-219.
[8] FENG C,YU S N.Content-based image retrieval by DTCWTfeature[J].2011 3rd International Conference on Computer Research and Development,2011,3(4):283-286.
[9] LIU B,ZHANG H.Image retrieval algorithm based on convolutional neural network and manifold ranking[J].Journal of Computer Applications,2016,6(2):531-534.(in Chinese) 刘兵,张鸿.基于卷积神经网络和流形排序的图像检索算法[J].计算机应用,2016,6(2):531-534.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!