Question

Need improvements in code for project and explain what contribution has made in the project

topic - Lane line detection opencv python

here are a other few suggestions for improvementif you can add some better improvement contribution so please add:

Tune the parameters: The performance of the current code might not be optimal for different scenarios. The threshold, minLineLength and maxLineGap values passed in cv.HoughLinesP() can be adjusted to improve the detection of lane lines. You can also experiment with other edge detection techniques such as Sobel, Scharr, Laplacian, etc.

Add ROI selection: The current code uses a fixed set of vertices to define the region of interest. You can improve this by allowing the user to select the region of interest dynamically.

Add lane smoothing: The lane detection in the current code is somewhat jittery. You can smooth the detected lane lines by averaging the slopes and intercepts of the detected lines over multiple frames.

if you can write better code with some contribution than better please write the code

Answer 1

To improve lane line detection with OpenCV and Python, you can tune parameters, add ROI selection, and implement lane smoothing.

Step-by-step explanation:

Lane Line Detection using OpenCV and Python

To improve the existing code for lane line detection using OpenCV and Python, here are a few suggestions:

1. Tune the parameters: Experiment with different threshold, minLineLength, and maxLineGap values to improve lane line detection in various scenarios. You can also try different edge detection techniques such as Sobel, Scharr, and Laplacian to enhance the accuracy.
2. Add ROI selection: Instead of using fixed vertices to define the region of interest, allow the user to dynamically select the ROI. This would make the code more flexible and adaptable to different road conditions.
3. Add lane smoothing: To reduce the jitteriness in the detected lane lines, average the slopes and intercepts of the detected lines over multiple frames. This will provide a smoother representation of the lane.

By implementing these improvements, you can enhance the performance and accuracy of lane line detection in your project.