结合立体和激光重建的高高光表面缺陷检测

Arpita Dawda, M. Nguyen
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引用次数: 2

摘要

产品检验是当前生产过程中不可缺少的工具。它有助于保持产品的质量,并通过消除废料损失来降低制造成本[1]。在现代,检测过程也需要自动化、快速和准确[2]。机器视觉是用于提供基于图像的自动检测和分析的技术和方法[3]。然而,高镜面(镜面状)表面仍然被证明是许多最先进的三维(3D)重建方法的局限性。外表面的高光性给产品模型的精确三维重建带来了困难。除了精确的测量外,检测产品中存在的凹痕、凸起、裂缝和划痕等缺陷也很重要。由于这些缺陷是可触摸的,相机是不可见的,因此在环境照明条件下使用基于视觉的检测技术很难检测到它们。本文提出了一种基于激光线投影和立体视觉的自动缺陷检测技术。这项研究活动是先前研究的演变,其中使用了立体视觉重建和激光线投影的思想,用于高镜面的精确3D测量。本文研究了在环境光照条件下三种缺陷类型(凹痕、划痕和凸起)的检测。最后,将缺陷产品的输出三维轮廓与非缺陷产品进行比较,以进行精度评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defects Detection in Highly Specular Surface using a Combination of Stereo and Laser Reconstruction
Product inspection is an indispensable tool of the current manufacturing process. It helps maintain the quality of the product and reduces manufacturing costs by eliminating scrap losses [1]. In the modern era, the inspection process also needs to be automatic, fast and accurate [2]. “Machine vision is the technology and methods used to provide imaging-based automatic inspection and analysis [3].” However, highly specular (mirror-like) surfaces are still proven to be the limitation of many state-of-art three-dimensional (3D) reconstruction approaches. The specularity of the outer surface makes it difficult to 3D reconstruct the product model accurately. Along with accurate measurements, it is also essential to detect defects such as dents, bumps, cracks and scratches present in a product. As these defects are palpable and are not visible by the camera, it is tough to detect them using vision-based inspection techniques in ambient lighting conditions. This paper presents an automated defect detection technique using the concepts of laser line projection and stereo vision. This research activity came up as an evolution of a previous study in which, the ideas of stereo-vision reconstruction and laser line projection were used, for accurate 3D measurement of highly specular surfaces. In this paper, the detection of three defect types (Dents, Scratches and Bumps) are examined in ambient lighting conditions. In the end, the output 3D profile of the defected product is compared with the non-defective product for accuracy evaluation.
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