摘要： 基于Gabor滤波器的纹理图像分割算法存在参数难以选择的问题。为此,提出一种预测图像纹理类型数与Gabor滤波器组参数的分割算法。将图像分割成大小相等的区域块,根据各类纹理特性预测Gabor滤波器组参数,利用各区域块的纹理特征向量预测纹理类型数,并使用预测的滤波器组提取图像纹理特征,通过预测的纹理类型数对图像进行聚类分割。实验结果表明,该算法能以较高的精度与较快的速度分割纹理图像,且受纹理类型数量影响较小。

关键词: Gabor滤波器, 纹理图像, 纹理类型, 灰度共生矩阵, 模糊C均值聚类

Abstract: To solve the problem of parameter selection in the algorithm of texture image segmentation based on Gabor filter,a texture image segmentation algorithm is proposed in this paper,which predicts the number of texture types and the parameters of Gabor filter bank.Firstly,the image is divided into regional blocks.Then,the number of texture types is predicted by the texture feature vector of regional blocks,and the parameters of Gabor filter bank are predicted by the characteristics of various texture features.Finally,texture features of the original image is extracted by using the predicted filter bank,and the image is clustered and segmented based on the predicted number of texture types.Experimental results show that the proposed algorithm can process the segmentation in the texture image with higher precision and faster speed,and is less affected by the number of texture types.

Key words: Gabor filter, texture image, texture type, Gray Level Co-occurrence Matrix(GLCM), Fuzzy C-means(FCM) clustering

中图分类号: 

• TP391.4