Modern automotive systems increasingly depend on camera sensors to gather safetycriticaldata used in driver-assisting features of the system. These features can consist offor example, lane-keeping assist and automatic braking where the sensors register objectswithin certain distances. When these camera sensors gather information, the time of theimage is critical for the calculation of speeds, distances, and size of any potential registeredobject in the frame. Limitations of bandwidth and computing in such vehicles creates aneed to use special cameras that do not capture the whole image simultaneously but insteadcapture the images piecewise. These cameras are called rolling shutter cameras. Thisputs pressure on defining when an image was captured when different parts of the imagewere captured at different points in time. For this thesis, this point in time is defined as thechronological middle point in between the camera starting to capture an image and when ithas collected the final part of it. This thesis performs a mapping-study to evaluate methodsto verify the timestamp of an image generated from rolling shutter cameras. Further, thisthesis proposes a new method using multiple digital clocks and presents its performanceusing a proof-of-concept implementation to prove the method’s ability to accurately representtime with sub-millisecond accuracy.