Department of Smart Mobility Engineering, Joongbu University, 305 Dongheon-ro, Deogyang-gu, Goyang-si 21713, Gyeonggi-do, Republic of Korea.
Sensors (Basel). 2023 Jun 6;23(12):5363. doi: 10.3390/s23125363.
We propose an algorithm for generating a panoramic image of a pipe's inner surface based on inverse perspective mapping (IPM). The objective of this study is to generate a panoramic image of the entire inner surface of a pipe for efficient crack detection, without relying on high-performance capturing equipment. Frontal images taken while passing through the pipe were converted to images of the inner surface of the pipe using IPM. We derived a generalized IPM formula that considers the slope of the image plane to correct the image distortion caused by the tilt of the plane; this IPM formula was derived based on the vanishing point of the perspective image, which was detected using optical flow techniques. Finally, the multiple transformed images with overlapping areas were combined via image stitching to create a panoramic image of the inner pipe surface. To validate our proposed algorithm, we restored images of pipe inner surfaces using a 3D pipe model and used these images for crack detection. The resulting panoramic image of the internal pipe surface accurately demonstrated the positions and shapes of cracks, highlighting its potential utility for crack detection using visual inspection or image-processing techniques.
我们提出了一种基于反向透视映射（Inverse Perspective Mapping，简称 IPM）生成管道内表面全景图像的算法。本研究的目的是生成管道内表面的全景图像，以便在不依赖高性能采集设备的情况下进行高效的裂纹检测。通过管道时拍摄的正面图像被转换为管道内表面的图像，使用 IPM 进行转换。我们推导出了一个广义的 IPM 公式，该公式考虑了图像平面的斜率，以纠正由平面倾斜引起的图像失真；该 IPM 公式是基于透视图像的消失点推导出来的，该消失点是使用光流技术检测到的。最后，通过图像拼接将具有重叠区域的多个变换图像组合在一起，以创建管道内表面的全景图像。为了验证我们提出的算法，我们使用 3D 管道模型恢复了管道内表面的图像，并使用这些图像进行了裂纹检测。生成的内部管道表面全景图像准确地显示了裂纹的位置和形状，突出了其在使用视觉检查或图像处理技术进行裂纹检测方面的潜在用途。
