The topic of this paper is making an ADAS algorithm in which cameras are used instead of conventional mirrors in vehicles. First, the existing solutions are presented based on scientific papers and examples from the automotive industry. Various cameras-related functionalities are shown as a mirror replacement for several car manufacturers. The proposed solution is based on the processing of signals received from five different cameras, using three wide and two narrow-angle cameras. The solution was implemented in the VISION SDK software framework using the ADAS Alpha board. The solution is written in the C programming language. Four use cases and one algorithm link were implemented. In use cases with two and three cameras, different views of the vehicle environment are shown. Such displays allow an overview of both blind spots around the vehicle and a very good overview of the rest of the surroundings. The use case with zooming in the desired part of the image allows the user to select the part of the screen he wants to enlarge. The user can choose between two different levels of zoom and can therefore be displayed on the screen. The last use case was used to detect the car, calculate the distance of the car from the camera and calculate the speed of the car. This use case is based on information about the height of the bounding box obtained from the car detector and on the basis of which the distance calculation of the car is performed. The speed estimate was performed based on the change in distance over an appropriate time interval. Verification of the operation of the algorithm was performed by measuring the FPS, observing the CPU load during execution and comparing the obtained results with the actual ones. After testing, it was concluded that the first three use cases work very reliably. The use case with car detection and calculating distance and speed works satisfactorily. The results depend entirely on the algorithm for detecting cars that is not always reliable in real conditions.