Road Extraction from Image using SVM?

Question

rizwan 2013-6-14

0
链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/79091-road-extraction-from-image-using-svm

评论： ROSE MARY KATIKALA 2017-3-20

Can any one help me to write code for road extraction from image using Support vector machine?

Any Help would be appreciated...

Thanks

8 个评论
显示 6更早的评论隐藏 6更早的评论

rizwan 2013-6-18

Thanks Jeff,

No got stuck in the svmtrain function, as matlab help suggests the first parameter is Training, how ?

As i have just used the imread() method to read the image and obtained the Array of image..

Yes Jeff you were write converting color image to grayscale prone to reduction of information about the image, i will continue with the color image i thought i would be good enough if have have just 0,1 values of pixels and make less effort in classification step but i was wrong

Thanks and appreciate Conversation and Learned Alot from your comments.

Jeff E 2013-6-18

This page: http://www.mathworks.com/help/stats/support-vector-machines-svm.html#bss0s6_-1

has two examples of how to train an SVM using two different 2-D data sets. If you are keeping things simple, and just using the RGB values of individual pixels, you should be able to follow these pretty closely.

impixel should facilitate generating your two training data sets.

If you run into problems following the examples, post your code and error messages generated to get more specific help. If everything goes smoothly, then you can look at additional kinds of training data (neighboring pixel info, texture, etc.)

请先登录，再进行评论。

请先登录，再回答此问题。

Answer 1

Image Analyst 2013-6-14

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/79091-road-extraction-from-image-using-svm#answer_88849

在 MATLAB Online 中打开

Pick your algorithm from Section 15 or 22 here: http://iris.usc.edu/Vision-Notes/bibliography/contents.html

Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following
Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities
Optical Flow Field Computations and Use
Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion
Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection
Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models
Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics
Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR

2 个评论
显示无隐藏无

Image Analyst 2013-6-15

OK, so you say you've read the several dozen papers listed there like "Road Extraction Based on the Algorithms of MRF and Hybrid Model of SVM and FCM", plus even more, and none of them work. Those people spent months developing their algorithms so I doubt I'm going to be able to give you anything after 5 minutes of work. I don't even know what the two clusters you want to use with the SVM represent. Please tell me what your clusters represent. Plus I don't know what your plans are to handle the fact that roads change color and the ground beside the roads also changes color.

rizwan 2013-6-18

Hi Image Analyst,

I said i have read the papers but none of any paper has given the implementation details just described the algorithm nothing else..i want some help from where i am able to implement Road Extraction using SVM, my research fellow told me about the svmlib and currently i m working on it.

请先登录，再进行评论。

Answer 2

Walter Roberson 2013-6-15

0
链接

此回答的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/79091-road-extraction-from-image-using-svm#answer_88918

Take the N x N window of pixels that has a given pixel in the center. Reshape that N x N window to be a vector. Now use that vector as one "sample". Do the same for each of the pixels in the image (after deciding how you want to handle the boundary conditions.)

If you are really lucky then a c-means or k-means clustering with two clusters will divide nicely into "road" versus "non-road". But I doubt you would be so lucky.

So now take a subset of the pixels and manually assign classes numbers to them, +1 for road, -1 for non-road. Train the subset with class number using your favorite 2-class technique (e.g., SVM). Now apply the learned metrics against a test class for which the answer is known but not input. Check the accuracy. If everything is okay, go ahead and apply to the entire image.

1 个评论
显示 -1更早的评论隐藏 -1更早的评论

ROSE MARY KATIKALA 2017-3-20

how can i assign +1 to roads and -1 to nonroads based on glcm texture feature calculation? can u please provide code. i have calculated entropy energy etc values and im comfused what to after that.

请先登录，再进行评论。