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首页> 外文期刊>International Journal of Image, Graphics and Signal Processing >Pavement Crack Detection Using Spectral Clustering Method
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Pavement Crack Detection Using Spectral Clustering Method

机译:基于谱聚类的路面裂缝检测

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摘要

Pavement crack detection plays an important role in pavement maintaining and management, nowadays, which could be performed through remote image analysis. Thus, edges of pavement crack should be extracted in advance; in general, traditional edge detection methods don’t consider phase information and the spatial relationship between the adjacent image areas to extract the edges. To overcome the deficiency of the traditional approaches, this paper proposes a pavement crack detection algorithm based on spectral clustering method. Firstly, a measure of similarity between pairs of pixels is taken into account through orientation energy. Then, spatial relationship is needed to find regions where similarity between pixels in a given region is high and similarity between pixels in different regions is low. After that, crack edge detection is completed with spectral clustering method. The presented method has been run on some real life images of pavement crack, experimental results display that the crack detection method of this paper could obtain ideal result.
机译:如今,路面裂缝检测在路面维护和管理中起着重要作用,可以通过远程图像分析来执行。因此,应提前提取路面裂缝的边缘。通常,传统的边缘检测方法不会考虑相位信息和相邻图像区域之间的空间关系来提取边缘。为克服传统方法的不足,提出一种基于谱聚类的路面裂缝检测算法。首先,通过取向能量考虑像素对之间的相似性的量度。然后,需要空间关系来找到给定区域中的像素之间的相似度高而不同区域中的像素之间的相似度低的区域。之后,利用光谱聚类方法完成裂纹边缘检测。该方法已经在一些实际的路面裂缝图像上进行了实验,实验结果表明本文的裂缝检测方法可以取得理想的效果。

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