FCM分割和形态学的沥青路面图像裂缝提取  

FCM segmentation and morphology based asphalt pavement image cracks extraction

作　　者：宋蓓蓓[1] 韦娜[1] 

机构地区：[1]长安大学信息工程学院,西安710064

出　　处：《计算机工程与应用》2013年第4期31-34,共4页Computer Engineering and Applications

基　　金：国家自然科学基金资助项目(No.60902075);中央高校基本科研业务费专项基金资助项目(No.CHD2012JC067;No.CHD2010JC056)

摘　　要：利用裂缝相对于路面的亮度、几何纹理等特征差异,提出了一种基于FCM图像分割和形态学的沥青路面图像裂缝提取方法。拍摄的路面图像经过去噪、亮度非均匀校正和对比度增强等一系列预处理,提高图像中裂缝与路面背景的差异。采用FCM方法分割图像,初步提取裂缝。利用膨胀、腐蚀和细化等形态学操作,对裂缝连通区域面积进行阈值判决实现裂缝的精细提取。实验结果表明,该综合方法获得了较好的检测结果,能有效地提取弱对比度的裂缝和细小裂缝。As the brightness, geometry and texture of the crack region is different from that of the road background, an asphalt pavement cracks extraction method using Fuzzy C-Means clustering （FCM） segmentation and morphology is proposed. A series of preprocessing including denoising, brightness non-uniformity correction and contrast enhancement are implemented, as the aim is to improve the differences between cracks and background. The FCM method is adopted to segment the image to realize the initial cracks extraction. The morphological operations consist of the dilation, erosion and thin are performed on the obtained image, and then the fine cracks extraction is realized by making threshold decision on the cracks connected area. The experimental results show that the proposed method can effectively extract the small cracks and the cracks with the weak contrast, and it has strong robustness and practical value.

关 键 词：道路工程 路面裂缝 预处理 模糊C均值聚类 形态学 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]