METHOD AND SYSTEM FOR DETECTING AND CLASSIFYING LANES

The present disclosure is related in general to field of machine learning and image processing, that provides a method and system for detecting and classifying lanes. A lane detection and classification system receives an input image from a data source and segments the input image into plurality of segments using a trained semantic segmentation model. Further, one or more lane markings are detected in the segmented image and, lane pattern and lane colour of each of the one or more lane markings, wherein each lane marking is associated with a priority. Subsequently, a binary image comprising lane markings of ego lanes of the host vehicle is generated and coefficient values of the ego lanes of the host vehicle are determined based on the priority value associated with the lane markings of the ego lanes and current position of the host vehicle, using a trained Convolutional Neural Network (CNN) model.