## 1 Introduction
The aim is to improve the existing classical approaches and techniques by determining some necessary scanning object characteristics. Such a solution could be developed by us and considered as a price-affordable complex vision system (compared with company solution) [13]. Figure 1: Purpose of cameras. This paper intends to show an approach for a simple vision system solution in terms of price and applicability to several cross-sectoral areas (manufacturing, assembly, and automotive). Contrary to passive and closed intelligent camera systems, embedded complex vision systems are significant for most machine vision applications in a small footprint. They are usually provided as units that deliver extensive processing power suited for industrial applications [14]. As a result, identification and subsequent navigation of the robotic arm become optimal and are maintained throughout the entire smooth automated operation. Nevertheless, some research and primary praxis demonstrated that the CCD sensor itself usually has, around the lens, a ring of red LEDs that serve as a passive light source [15]. Hoeever, additional lighting makes the solution more expensive on the one hand but increases the versatility and performance of work in the workplace. Despite this factor, we decided not to use the additional lightning and realize a solution based on the serial communication interface connected to the robotic arm control system. Different lighting was not considered, and the system compares the current and saved scene in real time according to the relevant lighting conditions. One crucial issue in the research of vision system usage is applied to the smartness, and the fast calibration is mainly followed for 3D measurement [16]. Therefore, this paper proposes a reachable vision system that will determine sensed object properties via communication between two CCD sensors, a processing unit, and a robotic design. This paper is divided into seven sections: Section 1 offers a review of the current deployment, research, and customer requirements for the vision system in general, as well as provides examples for their theoretic implementation. Existing technical solutions in this area focus on the progressive trends oriented on the various scanned parts to the sensing, following, and control as a whole. Section 2 deals with the available methods and procedures responsible for image processing followed by mathematical determination (epipolar geometry) regarding using 2D or 3D vision systems. Equally, in Section 3, there is an explanation of the proposed vision system that includes available communication interfaces, data transfer, and setup of the vision system itself. Finally, Section 4 consists of the framework for communication between the vision and control systems of the robotic arm, based on the communication RS232C channel. Part of this section is also the configuration and setting for the communication protocols, its composition, and an example for mutual communication between both sides (vision system and control system of robotic arm). Section 5 deals with the experimental setup of a technical solution based on two CCD systems, determinates its variables, and provides us with the experimental measurement for image processing. This section also includes the necessary steps for obtaining the object coordinates and the center of gravity from a sensed object that is also one of the leading research goals. The verification of the proposed solution is proven by the graphical and theoretical test of normality for each object coordinates. Section 6 focuses on summarizing and comparing our achieved results with actual relevant research in vision systems. This part of the article is focused on explaining the advantages and disadvantages of this presented solution with emphasis on its applicability and further development. At the same time, we present some professional solutions compared with our research in terms of usability and deployment in actual conditions.