Texture classification using Gabor wavelets based rotation invariant features
Texture classification using Gabor wavelets based rotation invariant features
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DOI：
10.1016/j.patrec.2006.05.008
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发表时间：
2006-12-01
影响因子：
5.1
通讯作者：
Priyal, S. Padam
中科院分区：
文献类型：
--
作者：
Arivazhagan, S.;Ganesan, L.;Priyal, S. Padam
基于纹理的图像分析技术已被广泛应用于遥感、地震道图像、医学图像的解译以及大型图像数据库中的按内容查询。小波变换等多分辨率分析技术的发展，促使人们开发出足够的工具来有效地刻画不同尺度的纹理。但是，小波变换缺乏将输入图像分解成多个方向的能力，这限制了其在旋转不变图像分析中的应用。提出了一种基于Gabor小波的旋转不变纹理分类新方法。Gabor小波是哺乳动物大脑视觉皮层细胞的数学模型，利用它可以将图像分解成多尺度、多方向。Gabor函数因其在空间域和频域的最优局部化特性而被公认为是纹理分析中非常有用的工具，并在计算机视觉中得到了广泛的应用。通过计算Gabor滤波后图像的均值和方差来发现纹理特征。旋转归一化是通过特征元素的循环移位来实现的，使得所有图像具有相同的主导方向。利用最小距离准则计算数据库中查询图像和目标图像的纹理相似度。(C)2006爱思唯尔B.V.保留所有权利。
Texture based image analysis techniques have been widely employed in the interpretation of earth cover images obtained using remote sensing techniques, seismic trace images, medical images and in query by content in large image data bases. The development in multiresolution analysis such as wavelet transform leads to the development of adequate tools to characterize different scales of textures effectively. But, the wavelet transform lacks in its ability to decompose input image into multiple orientations and this limits their application to rotation invariant image analysis. This paper presents a new approach for rotation invariant texture classification using Gabor wavelets. Gabor wavelets are the mathematical model of visual cortical cells of mammalian brain and using this, an image can be decomposed into multiple scales and multiple orientations. The Gabor function has been recognized as a very useful tool in texture analysis, due to its optimal localization properties in both spatial and frequency domain and found widespread use in computer vision. Texture features are found by calculating the mean and variance of the Gabor filtered image. Rotation normalization is achieved by the circular shift of the feature elements, so that all images have the same dominant direction. The texture similarity measurement of the query image and the target image in the database is computed by minimum distance criterion. (c) 2006 Elsevier B.V. All rights reserved.