Road Extraction from Image using SVM?
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Can any one help me to write code for road extraction from image using Support vector machine?
Any Help would be appreciated...
Thanks
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Jeff E
2013-6-18
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.)
回答(3 个)
Image Analyst
2013-6-14
Pick your algorithm from Section 15 or 22 here: http://iris.usc.edu/Vision-Notes/bibliography/contents.html
15 Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following
16 Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities
17 Optical Flow Field Computations and Use
18 Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion
19 Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection
20 Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models
21 Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics
22 Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR
2 个评论
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.
Walter Roberson
2013-6-15
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.
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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.
shantanu shukla
2014-4-20
Hay rizwan i am also working on it, so if u have some information related with road extraction then plz share with me.it's abt my project
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