Hough Transform-Based Lane Detection with Kalman Tracking

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Resource Overview

This package provides executable implementations of Hough transform-based lane detection, Kalman filter tracking algorithms, and other auxiliary programs featuring vehicle detection and traffic light recognition, offering comprehensive learning resources for computer vision applications.

Detailed Documentation

This package contains a robust Hough transform-based lane detection algorithm that efficiently identifies lane markings on road surfaces through edge detection and line parameter estimation. The implementation includes preprocessing steps such as region-of-interest selection and Canny edge detection, followed by probabilistic Hough line transformation to identify dominant lane boundaries. Additionally, the package incorporates Kalman filter tracking algorithms for vehicle motion trajectory prediction, utilizing state-space models to estimate position and velocity parameters. Other executable programs include vehicle detection using Haar cascades or YOLO-based approaches, and traffic light recognition through color segmentation and contour analysis. All programs are fully functional and serve as practical learning tools for understanding computer vision techniques and their real-world applications in autonomous driving systems.

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