:mortar_board: RESEARCH [:car: + :eyes:] Robust framework for Lane Detection and Tracking using Deep CNN, Extended Hough Transform and Kalman Filter for autonomous vehicle applications.

This project is to detect lane using deeplearning based segmentation(ICNet) and moving ROI. And it tracks lane using Kalman filter.

ROS2-based lane detection system for autonomous driving. It uses real-time video to detect and mark lanes with color overlays, provides an eagle view for enhanced accuracy, and integrates pattern recognition and image processing for robust lane tracking in automated systems.

This code can can perform robust lane detection and hand landmark tracking

Our final year project Lane Detection System for driving assistance which is robust and efficient system capable of detecting and tracking lane boundaries under diverse conditions.

Welcome to our Lane Detection repository, where cutting-edge image processing techniques are harnessed to achieve real-time identification and tracking of lanes on roadways. This repository hosts a comprehensive collection of code and resources to empower developers, researchers, and enthusiasts in implementing robust lane detection systems.

The main aim is to robustly detect a single lane boundary set from a monocular video Feed in real time and track car position relative to lanes, departure, entry, etc. We have used various edge detection methods for better tracking of lanes.

A Resilient Vision-Based Lane Detection System designed for reliable performance in diverse weather and lighting conditions. It integrates Bilateral Filtering, Adaptive Canny Edge Detection with Fuzzy Logic, Hough Transform, and Temporal Tracking for accurate detection. It provides a robust real-time solution for ADAS and autonomous driving.

This project demonstrates a comprehensive Computer Vision Perception System that combines multiple state-of-the-art techniques for autonomous vehicle perception. The system integrates lane detection, object detection, and multi-object tracking to create a robust perception pipeline suitable for autonomous driving applications.