Measurement viewpoint planning method for sheet metal parts with strong reflection

反射(计算机编程) 金属薄板 能见度 计算机科学 双向反射分布函数 曲面(拓扑) 航程(航空) 计算机视觉 光学 度量(数据仓库) 基质(化学分析) 全内反射 集合(抽象数据类型) 反射率 数学 材料科学 几何学 物理 数据挖掘 复合材料 程序设计语言
作者
Yue Su,Pan Zhang,Qingpeng Yang,Congjun Wang,Kai Zhong,Zhongwei Li
标识
DOI:10.1117/12.2666699
摘要

Limited by the imaging dynamic range of the camera, the phenomenon of over-exposure and over-dark often occurs in the 3D measurement of strong reflective sheet metal parts, resulting in incomplete measurement result. One of existing methods such as multiple exposure can measure most of the visible area under a single viewpoint, but the visible area with too small or too large incidence angle still cannot be measured. To solve this problem, in this paper, a method of viewpoint planning for sheet metal parts with strong reflection is proposed. The method introduces the surface reflection model of reflective sheet metal parts into viewpoint planning to achieve the synchronous optimum of measurement efficiency and data integrity. Firstly, according to the measurable region of the surface structured light 3D measurement system and CAD model, the candidate viewpoint set is randomly generated in the sampling space, and the visibility matrix is constructed by analyzing whether each candidate viewpoint is visible to each patch of the model. Then, the surface reflection model of sheet metal parts with strong reflection is constructed, and the reflection coefficient of the visible patches under each viewpoint is calculated according to the reflection model. Based on this, the measurability of the visible patches of the viewpoint under multiple exposures is calculated, and the visibility matrix is updated. Lastly, through the viewpoint quality evaluation function constructed based on the data coverage increment and multiple-exposure time, the viewpoint with the highest quality is selected heuristically until the coverage requirement is met. Experiments show that the algorithm can improve the measurement efficiency and ensure the integrity of the measurement data.
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