Help on SVM for road image processing I am new to SVM. I would like to use SVM to segment/cluster/classify a road image into two distinct regions i.e. drivable region and non-drivable region. Unfortunately, I do not have any images where the regions are already labeled.
I really don't know how to go about this i.e. specifying the training set.
Will weka be a good tool to use for the SVM?
Thanks in advance
 A: Have you read [3] yet? It can add to your understanding of both SVM and relevant features you might want to use on each image point. For each image point if you generate features on a neighbourhood around given point you should be able to distinguish between eg grass, gravel and tarmac. This will be computationally expensive though.
Other things I can think of is to use some edge detection algorithm, eg convolve the image with Sobel kernels to get X and Y gradients, prewitt or canny. Also try out different blob detection algorithms. After that you can use the hough transform[1,2] to find curves with different parameters (polynomials or splines perhaps).
In the hough space graph you would probably find curves matching road edges and lines in the middle of the road.
I recommend you read the book "Pattern Recognition and Machine Learning" by C. M. Bishop, Springer, 2007  and a book on computer vision of which I'm not the right person to suggest.
Weka is good to test different machine learning algorithms. For production use I recommend libSVM.
Please improve this question with references and be more specific on what you aim to accomplish.
There can be lots of stuff on/in a road.
I'm sorry for the formatting, it's written on my phone.


*

*Duda, R. O. and P. E. Hart, "Use of the Hough Transformation to Detect Lines and Curves in Pictures," Comm. ACM, Vol. 15, pp. 11–15 (January, 1972)

*D.H. Ballard, "Generalizing the Hough Transform to Detect Arbitrary Shapes", Pattern Recognition, Vol.13, No.2, p.111-122, 1981
http://www.cs.utexas.edu/~dana/HoughT.pdf

*Abenius, Tobias, "Classification of Cell Images Using MPEG-7-influenced Descriptors and Support Vector Machines in Cell Morphology", 2008
http://arxiv.org/abs/0812.2309
