基于改进Mask R-CNN和LSD的图纸管道检测方法

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

针对核电轴测视图中因管道特征不明显、管道尺度差异大及管道相交导致的管道识别精度差及错检、漏检等问题,提出一种基于改进的Mask R-CNN及LSD方法检测图纸中的管道。首先,针对管道特征不明显问题,将识别目标由管道调整为管道及其尺寸标注线,增加目标几何特征;其次,改进Mask R-CNN网络,引入双向加权特征金字塔结构,提高不同尺度目标特征提取能力,将原非极大值抑制改为DIoU-NMS,提高相交管道识别精度;最后,通过LSD算法检测出目标图像中的直线,再经过条件约束筛选及最小二乘拟合得到管道直线,实现管道的准确检测。实验结果表明,改进的Mask R-CNN算法有效减少了管道错检、漏检问题,精度可达90.04%,结合LSD直线检测、条件约束及最小二乘拟合算法得到管道直线,满足图纸管道检测的要求。

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.