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Three-dimensional measurement of small inner surface profiles using feature-based 3-D panoramic registration

机译:基于特征的3-D全景注册的小内表面型材的三维测量

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摘要

Rapid development in the performance of sophisticated optical components, digital image sensors, and computer abilities along with decreasing costs has enabled three-dimensional (3-D) optical measurement to replace more traditional methods in manufacturing and quality control. The advantages of 3-D optical measurement, such as noncontact, high accuracy, rapid operation, and the ability for automation, are extremely valuable for inline manufacturing. However, most of the current optical approaches are eligible for exterior instead of internal surfaces of machined parts. A 3-D optical measurement approach is proposed based on machine vision for the 3-D profile measurement of tiny complex internal surfaces, such as internally threaded holes. To capture the full topographic extent (peak to valley) of threads, a side-view commercial rigid scope is used to collect images at known camera positions and orientations. A 3-D point cloud is generated with multiview stereo vision using linear motion of the test piece, which is repeated by a rotation to form additional point clouds. Registration of these point clouds into a complete reconstruction uses a proposed automated feature-based 3-D registration algorithm. The resulting 3-D reconstruction is compared with x-ray computed tomography to validate the feasibility of our proposed method for future robotically driven industrial 3-D inspection.
机译:快速发展在复杂的光学组件,数字图像传感器和计算机能力的性能下以及降低成本使得能够使三维(3-D)光学测量能够更换制造和质量控制中的更传统的方法。 3-D光学测量的优点,如非接触,高精度,快速操作和自动化的能力,对内联制造非常有价值。然而,大多数电流光学方法都有资格用于外部而不是机加工部件的内表面。基于针对微小复杂内表面的三维型材测量的机器视觉提出了一种三维光学测量方法,例如内螺纹孔。为了捕获线程的完整地形范围(峰到谷),侧视商业刚性范围用于收集已知相机位置和方向的图像。利用测试件的线性运动,通过多视图立体声视觉生成三维点云,其通过旋转重复以形成额外的点云。将这些点云注册到完整的重建中使用了基于自动的特征的3-D注册算法。由此产生的3-D重建与X射线计算机断层扫描进行比较,以验证我们未来的机器人驱动的工业3-D检查的所提出方法的可行性。

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