Interactive Rapid Prototyping based on Computer Graphics for the Image Acquisition in Automated Visual Inspection

在这个项目中，我们将研究和开发使用合成生成的图像的基本概念和方法，以减少自动视觉检查(AVI)系统的设计、开发、实施和测试的高工作量，并提高其性能和健壮性。我们的新方法包括为这些目的使用计算机图形学(CG)创建的合成图像的基本和系统的调查。为此，我们的目标是为总体上的模拟方法创造一个坚实的科学基础，通过开发和定义适当的方法和标准来实现。这些结果有望在图像处理系统的众多任务中得到广泛的应用，更广泛地应用于传感器仿真领域。特别是，它们将促进和改进高性能和健壮的AVI系统的设计和评估，用于安全关键或质量敏感领域的应用。与以前的方法不同，我们将利用从图像生成过程中获得的信息来指导AVI系统的优化，从而显著改进和加速优化。例如，在CG的图像合成过程中，物体和照明之间的可见性以及设置内的整个光流是已知的，并且可以用于寻找AVI系统的最优图像采集设置。与以前的工作的另一个不同之处在于，引入了针对图像序列的图像采集组件的外部和内部参数以及最优图像数量的交互式和(部分)自动优化过程。在此过程中，首先由AVI专家选择将使用的目视检查方法。为了最佳地确定采集设置的众多参数，基于从图像合成获得的信息执行自动参数优化；只有当专家因为不满意的结果而决定这样做时，才由专家修改检查方法。这种任务分担将专家的能力和基于CG的自动优化的优势以一种富有成效的方式结合在一起。在这个拟议的联合项目中，三个研究所的合作，每个研究所都在各自的研究领域提供相关的专业知识，使这一跨学科主题的探索成为可能，这是以前的方法所没有达到的彻底。因此，我们期待的结果也适用于广泛的应用。

In this project, we will research and develop basic concepts and methods to use synthetically generated images for reducing the high effort for design, development, implementation, and testing of systems for automated visual inspection (AVI) and to increase their performance and robustness. Our new approach comprises a fundamental and systematic investigation of the use of synthetic images, created by means of computer graphics (CG), for these purposes. To this end, our goal is to create a solid scientific foundation for simulation approaches in general, to be achieved by developing and defining appropriate methods and criteria. These results are expected to find broad applications in numerous tasks of image processing systems, and also more generally in the field of sensor simulation. In particular, they will facilitate and improve the design and evaluation of high-performance and robust AVI systems for applications in safety critical or quality sensitive areas.In contrast to previous approaches, we will utilize information which is available from the image generation process for a guided, and thus significantly improved and accelerated, optimization of AVI systems. As an example, the visibility between objects and illumination as well as the entire flow of light within the setup are known during the image synthesis in CG and can be used to find the optimal image acquisition setup of the AVI system.Another difference to previous works is the introduction of an interactive and (partially) automated optimization process for the image acquisition components extrinsic and intrinsic parameters as well as the optimal number of images for image sequences. Within this process, first the visual inspection method which will be used is selected by an AVI-expert. In order to optimally determine the numerous parameters of the acquisition setup, an automated parameter optimization based on the information obtained from the image synthesis is performed; the inspection method is only modified by the expert, when she/he decides to do so because of unsatisfactory results. This task sharing combines the competence of the expert and the advantages of an automated optimization based on CG in a productive way.In this proposed joint project, the cooperation of three institutes, each of them providing relevant expertise in the respective research area, makes it possible to explore this interdisciplinary topic with a thoroughness which has not been reached by previous approaches. In consequence, we expect results which are also applicable for a wide range of applications.