应用光学, 2016, 37 (3): 402, 网络出版: 2016-10-20   

基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
作者单位
北京化工大学 信息科学与技术学院, 北京 100029
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.

王颖, 吴峰, 付国平. 基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. 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.

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