Lane detection using the concept of Deep learning and Digital image processing

Lane detection technology plays a pivotal role in enabling autonomous navigation in vehicles. However, existing systems primarily cater to well-structured roads with clear lane markings, rendering them ineffective in scenarios where markings are unclear or absent. This study critically evaluates an existing approach for detecting lanes on unmarked roads, followed by the proposal of an enhanced methodology. Both approaches leverage digital image processing techniques and rely solely on vision or camera data. The primary objective is to derive real-time curvature values to facilitate driver-assistance systems in making necessary turns and preventing vehicles from veering off-road.