Semi-Subsampled Contourlet Retrieval Algorithm Using Three Statistical Features

摘要：

In order to improve the retrieval rate of contourlet transform retrieval system,a semisubsampled contourlet transform based texture image retrieval system was proposed．In the system，the contourlet transform was constructed by non-subsampled Laplacian pyramid cascaded by critical subsampled directionaI filter banks,subbands standard deviation,absolute mean energY and kurtosis in semi—subsampled contourlet domain are cascaded to form feature vectors,and the similariry metric is Canberra distance．Experimental results on 109 brodatz texture images show that using the three cascaded features can lead to a higher retrieval rate than the combination of standard deviation and absolute mean which is most commonly used today under same dimension of feature vectors． Semi-subsampled contourlet transform based image retrieval system is superior to those of the original contourlet transform，non-subsampled contourlet system under the same system structure with same length of feature vectors． retrieval time and memon，needed,decomposition structure parameters can also make significant effects on retrieval rates，especially scale number．

关键词： content based image retrieval contourlet-stransform texture image standard deviation absolute mean energy kurtosis

作者: Yu-xi Liu Xin-Wu Chen

作者单位: Software College Zhengzhou University of Light Industry Zhengzhou,China College of Physics and Electronic Engineering Xinyang Normal University Xinyang,China

会议类型: 国际会议

会议名称: 2011 International Conference on Manufacturing and Industrial Engineering(ICMIE 2011)(2011年制造及工业工程国际会议)

会议地点: 海口

会议语种:英文

页码: 276-280

在线出版日期: 2011-02-22（万方平台首次上网日期，不代表论文的发表时间）