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Hi,

I use hough transform for straight lane detection but I got lots of false positives even in clear lane markings. My approach is like this:

1. Select ROI for near field
2. Eliminate noise (various options like gaussian, median filter...)
3. Detect edges and binarize image
4. Detect Hough lines
5. Eliminate lines considering the angle of the lines (different angles for left and right side of image)
6. Group Hough lines and draw bounding box around them
7. Track bounding boxes with Kalman filter

I am stuck with 5th and 6th step. Some of the lines, which are very close to each other, are drawn on the lane markings. How can I distinguish these lines and the others that are not on the lane markings?

I also wonder if hough transform is a really good idea for straight lines. Maybe I need to use RANSAC for fitting. Any suggestions?

Regards

Hi,

I use hough transform for straight lane detection but I got lots of false positives even in clear lane markings. My approach is like this:

1. Select ROI for near field
2. Eliminate noise (various options like gaussian, median filter...)
3. Detect edges and binarize image
4. Detect Hough lines
5. Eliminate lines considering the angle of the lines (different angles for left and right side of image)
6. Group Hough lines and draw bounding box around them
7. Track bounding boxes with Kalman filter

I am stuck with 5th and 6th step. Some of the lines, which are very close to each other, are drawn on the lane markings. How can I distinguish these lines and the others that are not on the lane markings?

I also wonder if hough transform is a really good idea for straight lines. Maybe I need to use RANSAC for fitting. Any suggestions?

This is very simple image from Caltech Lanes Dataset. However, I don't work on single images but image sequences under changing lighting conditions.

Regards

Hi,

I use hough transform for straight lane detection but I got lots of false positives even in clear lane markings. My approach is like this:

1. Select ROI for near field
2. Eliminate noise (various options like gaussian, median filter...)
3. Detect edges and binarize image
4. Detect Hough lines
5. Eliminate lines considering the angle of the lines (different angles for left and right side of image)
6. Group Hough lines and draw bounding box around them
7. Track bounding boxes with Kalman filter

I am stuck with 5th and 6th step. Some of the lines, which are very close to each other, are drawn on the lane markings. How can I distinguish these lines and the others that are not on the lane markings? I also wonder if hough transform is a really good idea for straight lines. Maybe I need to use RANSAC for fitting. Any suggestions?

This is very simple image from Caltech Lanes Dataset. However, I don't work on single images but image sequences under changing lighting conditions.

Regards