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A Study on the Improved Line Detection Method for Pipeline Recognition of P&ID  

Oh, Sangjin (Digital Innovation Dept, Hyundai Engineering)
Chae, Myeonghoon (Digital Innovation Dept, Hyundai Engineering)
Lee, Hyun (Digital Innovation Dept, Hyundai Engineering)
Lee, Younghwan (Engineering Center, Hyundai Engineering)
Jeong, Eunkyung (Engineering Center, Hyundai Engineering)
Lee, Hyunsik (Digital Innovation Dept, Hyundai Engineering)
Publication Information
Plant Journal / v.16, no.4, 2020 , pp. 33-39 More about this Journal
Abstract
For several decades, productivity in construction industry has been regressed and it is inevitable to improve productivity for major EPC players. One of challenges to achieve this goal is automatically extracting information from imaged drawings. Although computer vision technique has been advanced rapidly, it is still a problem to detect pipe lines in a drawing. Earlier works for line detection have problems that detected line elements be broken into small pieces and accuracy of detection is not enough for engineers. Thus, we adopted Contour and Hough Transform algorithm and reinforced these to improve detection results. First, Contour algorithm is used with Ramer Douglas Peucker algorithm(RDP). Weakness of contour algorithm is that some blank spaces are occasionally found in the middle of lines and RDP covers them around 17%. Second, HEC Hough Transform algorithm, we propose on this paper, is improved version of Hough Transform. It adopted iteration of Hough Transform and merged detected lines by conventional Hough Transform based on Euclidean Distance. As a result, performance of Our proposed method improved by 30% than previous.
Keywords
P&ID; Computer vision; Line recognition; Hough transform;
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  • Reference
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