This research involves using an object recognition system and an ancillary image sensor to detect lane markers and zebra crossings on a roadway in a vehicle. To perform this detection, these steps have been followed: take a picture of the scene, digitize it, normalize it, define a search area within it, look for lane and zebra markers within it. The Lane Tracking for Driving System was created to assist drivers in making lane departure decisions, to lessen concentration breaks, and to avoid accidents while driving. To offer a way to detect a specific traffic violation-namely, stopping on a zebra crossing at a traffic signal rather than following behind it-and to offer a workaround. In the proposed work, systems are implemented and improved using adaptive algorithms. MATLAB's image processing toolbox is used to design and implement the proposed algorithm.