王颖, 吴峰, 付国平. 于散乱三维点云的缺陷检测和三维重构方法[J]. 应用光学, 2016, 37(3): 402-406. DOI: 10.5768/JAO201637.0303001
引用本文: 王颖, 吴峰, 付国平. 于散乱三维点云的缺陷检测和三维重构方法[J]. 应用光学, 2016, 37(3): 402-406. DOI: 10.5768/JAO201637.0303001
Wang Ying, Wu Feng, Fu Guoping. Method for defects detection and 3D reconstruction based on dispersed points cloud[J]. Journal of Applied Optics, 2016, 37(3): 402-406. DOI: 10.5768/JAO201637.0303001
Citation: Wang Ying, Wu Feng, Fu Guoping. Method for defects detection and 3D reconstruction based on dispersed points cloud[J]. Journal of Applied Optics, 2016, 37(3): 402-406. DOI: 10.5768/JAO201637.0303001

于散乱三维点云的缺陷检测和三维重构方法

Method for defects detection and 3D reconstruction based on dispersed points cloud

  • 摘要: 设备表面的缺陷检测对于保证安全生产避免经济损失具有重要意义。针对基于设备表面散乱三维点云缺陷检测和三维重构算法复杂的问题,提出了一种基于散乱三维点云的缺陷检测和三维重构方法。对散乱三维点云沿某一轴向进行分层处理,将同一层内的三维点进行移位规则化处理,并对规则化的三维点云进行缺陷检测和三维重构。分别对无缺陷设备表面和凹凸缺陷设备表面进行缺陷检测和三维重构,规则化前后三维数据缺陷计算结果相对误差为1.01%。实验结果表明,将散乱三维点云分层和规则化处理有效降低了缺陷检测和三维重构的复杂度,易于实现。

     

    Abstract: Equipment surface defect detection is very important for ensuring safety production and avoiding economic losses. Aiming at the algorithm complexity problem of defect detection and 3D reconstruction for dispersed 3D points on the equipment surface, a new method was proposed. All the points were divided into different layers along to the axis, then the points on the layer were moved to the middle plane of the layer. The distribution of the points became regularly and the defect detection and 3D reconstruction were done by the points regularized. The dispersed points defects detection and 3D reconstructions were fulfilled and the error of the defection detection is 1.01%. Experimental results show that this defection detection method proposed is simple and easy to implement after the dispersed points are regularized.

     

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