基于图像分析的飞机蒙皮裂纹检测

为实现飞机蒙皮裂纹的自动检测,在通过云台搭载长焦成像系统进行扫描成像的基础上,研究蒙皮图像处理与裂纹参数提取算法。针对飞机蒙皮图像的特点,首先通过光照一致化、自适应灰度拉伸、分区大津(OTSU)法阈值分割等处理得到裂纹的二值化图像;然后利用连通域的面积、矩形度等特征剔除块噪声;在去噪的基础上,对二值化图像中的裂纹部分进行细化、去毛刺等操作,并通过去节点获取各条裂纹枝干;最后以枝干像素为索引,逐点跟踪获取各条裂纹枝干的长度、平均宽度、最大宽度、起点坐标、终点坐标、中心坐标、裂纹走向及数目等信息并由检测软件输出裂纹检测报告。实验结果表明,所提方法可有效检测宽度大于1 mm的蒙皮表面裂纹,为飞机机身和机翼蒙皮表面裂纹的自动检测提供了一种可行手段。

Crack detection for aircraft skin based on image analysis

To realize automatic crack detection for aircraft skin, skin image processing and parameter estimation methods were studied based on scanning images obtained by pan-and-tilt long-focus camera. Firstly, considering the characteristics of aircraft skin images, light compensation, adaptive grayscale stretching, and local OTSU segmentation were carried out to obtain the binary images of cracks. Then, the characteristics like area and rectangularity of the connected domains were calculated to remove block noises in the images. After that, thinning and deburring were operated on cracks presented in the denoised binary images, and all branches of crack were separated by deleting the nodes of cracks. Finally, using the branch pixels as indexes, information of each crack branch such as the length, average width, maximum width, starting point, end point, midpoint, orientation, and number of branches were calculated by tracing pixels and the report was output by the crack detection software. The experimental results demonstrate that cracks wider than 1 mm can be detected effectively by the proposed method, which provides a feasible means for automatic detection of aircraft skin cracks in fuselage and wings.