Computer and Modernization ›› 2024, Vol. 0 ›› Issue (10): 42-48.doi: 10.3969/j.issn.1006-2475.2024.10.007

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Pipelines in Drawings Detection Method Based on Improved Mask R-CNN and LSD 

  

  1. (1. College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 201306, China;
    2. China Nuclear Industry Fifth Construction Co., Ltd., Shanghai 201500, China)
  • Online:2024-10-29 Published:2024-10-30

Abstract: Aiming at the problems of poor precision of pipelines detection, false detection and missed detection  caused by indistinct pipelines features, large differences in pipeline scales and pipeling intersections in the nuclear power axonometric drawings,an method for pipelines detection based on improved Mask R-CNN and LSD is proposed. Firstly, aiming at the problems of indistinct pipelines features, the recognition target is adjusted from the pipelines to the pipelines and its dimensioned lines. The recognition target geometry features are added. Secondly, the Mask R-CNN network is improved, and the BiFPN structure is used to enhance the ability to extract target features at different scales. We change the original NMS to DIoU-NMS to improve the accuracy of intersecting pipelines detection. Finally, the LSD algorithm is used to detect the lines in the target image, and then the pipeline lines are obtained by conditional constraint filtering and least square fitting. The experimental results show that the improved Mask R-CNN algorithm can well solve the problems of missed detection and false detection, and its accuracy recognition rate reaches 90.04%. Combining LSD line detection, conditional constraint, and least squares fitting algorithm, pipeline lines are obtained, which meets the requirements of pipelines detection in the drawings.

Key words:  , pipelines detection, instance segmentation, Mask R-CNN algorithm, LSD, conditional constraint

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