Advanced Driver Assistance Systems (ADAS) have become an integral part of modern vehicles, with the potential to significantly enhance safety on the road. ADAS technology involves the use of sensors, algorithms, and software to assist drivers and provide them with real-time information about their surroundings, traffic conditions, and potential hazards. Sensors utilized for object tracking and environmental detection, particularly those based on laser, radar, and camera technologies, are fundamental to the functional performance of ADAS. Within automotive applications, the majority of camera systems are equipped with wide-angle or fish-eye lenses, both of which are known to introduce substantial optical distortion. To ensure accurate environmental perception, particularly in the context of geometric feature recognition and distance estimation, such cameras require meticulous calibration. Therefore, this paper describes a case study concerning cameras used in vision-based ADAS, as well as the most frequently used calibrating techniques. It describes the fundamentals of camera calibration and implementation, with results given for different lenses and distortion models. By engaging with this article, readers will gain a comprehensive understanding of the technological foundations, functional principles, and practical challenges associated with camera-based ADAS that need to be addressed to ensure its safe and effective operation on the road. The article serves as a technical reference that not only enhances the reader’s theoretical knowledge but also informs practical decision-making in the development of safe and effective driver assistance systems.