UNSUPERVISED TEXTURE SEGMENTATION USING GABOR FILTERS
UNSUPERVISED TEXTURE SEGMENTATION USING GABOR FILTERS
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DOI：
10.1016/0031-3203(91)90143-s
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发表时间：
1991-01-01
影响因子：
8
通讯作者：
FARROKHNIA, F
中科院分区：
文献类型：
--
作者：
JAIN, AK;FARROKHNIA, F
本文提出了一种基于多通道滤波理论的纹理分割算法。信道的特征在于由几乎均匀地覆盖空间-频率域的一组Gabor滤波器，并且提出了一种系统的滤波器选择方案，该方案基于从滤波图像重建输入图像。纹理特征是通过对每个（选择的）滤波图像进行非线性变换并计算每个像素周围窗口中的“能量”来获得的。然后使用平方误差聚类算法来整合特征图像并产生分割。一个简单的程序，将空间信息的聚类过程中提出。一个相对指数是用来估计“真实”的纹理类别的数量。
This paper presents a texture segmentation algorithm inspired by the multi-channel filtering theory for visual information processing in the early stages of human visual system. The channels are characterized by a bank of Gabor filters that nearly uniformly covers the spatial-frequency domain, and a systematic filter selection scheme is proposed, which is based on reconstruction of the input image from the filtered images. Texture features are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of "energy" in a window around each pixel. A square-error clustering algorithm is then used to integrate the feature images and produce a segmentation. A simple procedure to incorporate spatial information in the clustering process is proposed. A relative index is used to estimate the "true" number of texture categories.