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使用新型旋转复小波滤波器的纹理图像检索

Texture image retrieval using new rotated complex wavelet filters.

作者信息

Kokare Manesh, Biswas P K, Chatterji B N

机构信息

Department of Electronics and Electrical Communication Engineering, Indian Institute of Technology, Kharagpur, India.

出版信息

IEEE Trans Syst Man Cybern B Cybern. 2005 Dec;35(6):1168-78. doi: 10.1109/tsmcb.2005.850176.

Abstract

A new set of two-dimensional (2-D) rotated complex wavelet filters (RCWFs) are designed with complex wavelet filter coefficients, which gives texture information strongly oriented in six different directions (45 degrees apart from complex wavelet transform). The 2-D RCWFs are nonseparable and oriented, which improves characterization of oriented textures. Most texture image retrieval systems are still incapable of providing retrieval result with high retrieval accuracy and less computational complexity. To address this problem, we propose a novel approach for texture image retrieval by using a set of dual-tree rotated complex wavelet filter (DT-RCWF) and dual-tree-complex wavelet transform (DT-CWT) jointly, which obtains texture features in 12 different directions. The information provided by DT-RCWF complements the information generated by DT-CWT. Features are obtained by computing the energy and standard deviation on each subband of the decomposed image. To check the retrieval performance, texture database D1 of 1856 textures from Brodatz album and database D2 of 640 texture images from VisTex image database is created. Experimental results indicates that the proposed method improves retrieval rate from 69.61% to 77.75% on database D1, and from 64.83% to 82.81% on database D2, in comparing with traditional discrete wavelet transform based approach. The proposed method also retains comparable levels of computational complexity.

摘要

设计了一组新的二维(2-D)旋转复小波滤波器(RCWF),其具有复小波滤波器系数,可给出在六个不同方向上强烈定向的纹理信息(与复小波变换相隔45度)。二维RCWF不可分离且定向,这改善了对定向纹理的表征。大多数纹理图像检索系统仍然无法提供具有高检索精度和低计算复杂度的检索结果。为了解决这个问题,我们提出了一种新颖的纹理图像检索方法,通过联合使用一组双树旋转复小波滤波器(DT-RCWF)和双树复小波变换(DT-CWT),该方法可在12个不同方向上获取纹理特征。DT-RCWF提供的信息补充了DT-CWT生成的信息。通过计算分解图像每个子带的能量和标准差来获得特征。为了检验检索性能,创建了来自Brodatz相册的1856个纹理的纹理数据库D1和来自VisTex图像数据库的640个纹理图像的数据库D2。实验结果表明,与传统的基于离散小波变换的方法相比,该方法在数据库D1上的检索率从69.61%提高到77.75%,在数据库D2上从64.83%提高到82.81%。该方法还保持了相当水平的计算复杂度。

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