I'm working on a project that includes lane detection and tracking;
I'm able to detect straight lines in image using HT; I'd like to know how to accurately detect and fit curved lines in an image. Thanks folks
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Hi eric.My project is exactly like you but im using the b-snake rather than HT.Can I know how you removed the unwanted background such as trees and shadows from the road? What is suitable technique that you use ? I really hope for your reply.Tq
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If you have the coordinates of the pixels, you could use polyfit to fit them to a polynomial.
See articles on road following: Vision Bib
thanks, the pb is i don't hv those coordinates! i'm able to detect straight lines in binary image using HT without having to manually determine the coordinates of the pixels so I'd like to detect curved lines as well. when the road is flat the algorithm works well but the detection and fitting process become inaccurate when i deal with curved road. it's more like a parabola fitting problem i guess.
Well, maybe use the algorithm J recommended above or pick one from the exhaustive list I gave in Vision Bib. Or start simply with an edge detection routine, like the edge() function in MATLAB. Of course getting those coordinates is required before fitting to a curve can be done - you have to have something to fit to.
See info here: http://www.mathworks.com/matlabcentral/answers/63308#answer_74911
Hough Transform can also be used for detecting curves:http://faculty.washington.edu/cfolson/papers/pdf/cviu99.pdf
Thanks a lot for your quick reply J, I've read the paper but frankly speaking it's been kinda difficult for me to derive a working code based on that paper within these days. Can u direct me to a working code for curve fitting? not necessarily based on HT of course. the ones I hv can only detect straight lines and no curves!
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