In this OpenCV project, the primary objective is to
enhance the visibility of lined-up cones in
images to aid autonomous cars. Using C++
and the OpenCV library, I focused on detecting and drawing lines across the cones, providing a
clear reference path for the autonomous
vehicles. This project aimed to improve navigation safety, avoid collisions, and
ensure a smooth and accurate trajectory for efficient and secure autonomous driving.
//Here is a link to the code
//Features
Employed versatile image processing techniques, including
blurring, HSV thresholding, and contour extraction, to enhance the visibility of bright
orange cones, enabling improved navigation and obstacle avoidance for autonomous vehicles.
The enhanced reference paths can be utilized in autonomous
vehicles to improve navigation and obstacle avoidance, enhancing their safety and
reliability.
The image processing techniques automatically detect and isolate bright orange cones,
reducing the need for manual intervention.
With optimized algorithms, the project is capable of processing images
in real-time, making
it suitable for applications that require immediate responses.
The HSV thresholding method can be fine-tuned for detecting other
specific colors or objects in different scenarios.