An algorithm to detect and identify defects of industrial pipes using image processing

This paper proposes an effective algorithm for detecting and distinguishing defects in industrial pipes. In many of the industries, conventional defects detection methods are performed by experienced human inspectors who sketch defect patterns manually. However, such detection methods are much expensive and time consuming. To overcome these problems, a method has been introduced to detect defects automatically and effectively in industrial pipes based on image processing. Although, most of the image-based approaches focus on the accuracy of fault detection, the computation time is also important for practical applications. The proposed algorithm comprises of three steps. At the first step, it converts the RGB image of the pipe into a grayscale image and extracts the edges using Sobel gradient method, after which it eliminates the undesired objects based on their size. Secondly, it extracts the dimensions of the pipe. And finally this algorithm detects and identifies the defects i.e., holes and cracks on the pipe based on their characteristics. Tests on various kinds of pipes have been carried out using the algorithm, and the results show that the accuracy of identification rate is about 96% at hole detection and 93% at crack detection.