Research on defect inspection method of pipeline robot based on adaptive image enhancement

Abstract

In view of the problem about uneven image acquisition and inaccurate edge extraction in pipeline detection process, a pipeline robot defect inspection method based on adaptive image enhancement is proposed. Firstly, a single-scale Retinex adaptive image enhancement algorithm is designed, which uses the guided filter to estimate the illumination component of the Value component of the image, and gets the illumination equilibrium image by adaptive Gamma correction, so as to realize the image enhancement. Then, the traditional Canny edge detection method is improved, using bilateral filtering to smooth the image. Besides, the defect images are segmented by the iterative threshold method, and the edge connection is carried out according to the edge pixel similarity. Therefore, the defect contour of the pipe-wall is extracted effectively. Thirdly, a pipeline robot defect detection system based on adaptive image enhancement is built, and a crawler car equipped with the pan-tilt-zoom camera conducts all-round visual inspection of the defects in the pipeline inner wall. The experimental results show that the detection method in this paper can adaptively correct the image brightness, and the uneven brightness of the image is significantly improved. Compared with the sub-optimal algorithm, the information entropy of the image is increased by 2.4%, the average gradient of the image is increased by 2.3%, and the peak signal to noise ratio is increased by 4.4%, and the pipeline defect edges are extracted effectively with the detection accuracy up to 97%.