上海大学学报(自然科学版) ›› 2008, Vol. 14 ›› Issue (6): 551-556 .

• 通信与信息工程 •    下一篇

应用Gabor纹理特征的水管内壁图像分类

杨潇茜,王朔中   

  1. (上海大学 通信与信息工程学院,上海 200072)
  • 收稿日期:2007-07-06 修回日期:1900-01-01 出版日期:2008-12-21 发布日期:2008-12-21
  • 通讯作者: 王朔中

Image Classification for Sewer Duct Inspection Using Gabor Filtering

YANG Xiao-qian, WANG Shuo-zhong   

  1. (School of Communication and Information Engineering, Shanghai University, Shanghai 200072, China)
  • Received:2007-07-06 Revised:1900-01-01 Online:2008-12-21 Published:2008-12-21
  • Contact: WANG Shuo-zhong

摘要:

Gabor滤波器在图像分析和机器视觉方面得到广泛应用.将Gabor滤波用于识别地下水管内壁图像,对管壁损坏程度进行分类.针对Gabor函数之间的非正交性,优化参数,尽量减少滤波输出数据中的冗余信息,使用一组不同频率响应和角度特性的Gabor滤波器获取图像块纹理信息,并用主分量分析(principal components analysis, PCA)对得到的高维特征向量进行降维.对提取的纹理特征进行k-均值聚类,实验结果验证了该方法的有效性.

关键词: Gabor滤波器, 图像识别, 纹理特征

Abstract:

Gabor filters are widely used in image analysis and computer vision applications. We use a set of multiscale and multiorientation Gabor filters to extract texture features from image blocks of underground sewer duct, and use principal components analysis (PCA) to reduce dimension of the feature vectors. These feature vectors are related to the nature and extend of the damage in the sewerage. Classification of the image blocks is made based on the extracted feature vectors. As the Gabor filters are not orthogonal, suitable parameters should be chosen to minimize redundancy in the extracted image data. The result of k-means clustering verifies the validity of the proposed method. 

Key words: Gabor filter, image recognition, texture feature

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