# Vision System in Product Quality Control Systems
## 3 Discussion  
Vision systems support automation across a whole range of tasks performed on production lines. They are a source of data about the quality of the product for TQM quality management systems and MES production management. Their rapid development has been noticeable both in the scope of the realized control functions and the efficiency of image analysis. The development of 2D image analysis methods and the development of 3D image acquisition and analysis methods have resulted in the expansion of the number of measurement and control tasks that can be performed in industrial conditions. A simultaneous increase in the set of controlled parameters and a reduction in inspection time were observed. The automation of inspection operations using vision systems ensures the maintenance of the repeatability of the assessment of parameters describing the quality of a product and improves the effectiveness of the evaluation in relation to a visual inspection carried out by operators. The development of vision systems toward equipping them with I/O systems, communication protocol HMI interfaces, and databases makes it possible to integrate them directly into industrial automation systems and quality and production tracking and management systems. Building an industrial product vision system for 2D imaging involves selecting a sensor array and optics to achieve the desired imaging field and measurement resolution. Based on research and engineering knowledge, quality control and measurement algorithms can be implemented for the system. For 3D imaging systems, however, there are some limitations due to the availability of hardware such as high-resolution ToF arrays. Limitations also arise from the imaging method itself. For each inspection task, a feasibility study of the task must be carried out and a suitable imaging method selected (Figure 6). When building hybrid imaging systems, the limitations of all methods used in the construction of the product image must be taken into account. Figure 6: Resolution in 3D imaging methods. The increasing use of vision systems in quality control systems results from the dynamic growth observed in many fields of science and technology. The most significant influence on the development of all imaging techniques and their use in systems of product quality control are as follows:  
* Development of image registration methods is defined by the development and availability of a wide range of 2D sensors allowing for the registration of visible light, infrared, and ultraviolet including hyperspectral cameras after combining the fields. The development of 3D imaging technologies include laser triangulation, stereovision, structured light, TOF, SFF methods, and stereo photometry;
* Developments in optics result in lenses for different sensor formats that also enable imaging at various resolutions and the availability of lenses specialized for post-measurement tasks (e.g., telecentric, custom-made for a selected field of view);
* Development of technical lighting methods and lightning sources for vision systems. The large availability of illuminators allows for the selection of a solution to the control and measurement task;
* Development of processor technology and communication interfaces including in industrial systems, mainly USB Vision, Giga Vision, and Camera Link technologies, allow for the increase in the frequency of the data registration and analysis;
* Development of image analysis algorithms available in various types of post-programming for building industrial vision projects and in the form of vision libraries available in the currently used programming languages. In what has been described as Industry 4.0, there has been a strong emphasis on introducing cyber-physical systems to monitor production processes. The aim is to create a virtual copy of real objects for data analysis and decision-making. In the Internet of Things, cyber-physical systems make it possible to build communication links that allow different systems and people to work together.