Support Vector MAchine
I am new to SVM. I studied about using SVM from documentaion. and for working with images i refered "using OpenCV and SVM with images".
In documentation i understand the operation of SVM using coding. In "Using OpenCV and SVM with images" working with various image is discussed.
My application is to classify the feature extracted from my image with the image stored in memory. I use basic operations to get my ROI and calculated Hu-moments. is it possible to use SVM for my application as classifier?
sure this is possible (and a valid idea). try to code it, and come back, if you hit an obstacle.
your train-matrix will be N rows, each of them a humoment, your test-matrix will be a singe row(humoment).
yep that will work. I succeeded in building it for a HSV average value from a region descriptor, so it will work perfectly in your case.
@jamesnzt, were you using 2.4.9 or 3.0 ?
@berak 2.4.9
i have a doubt! While training SVM we give the training data (already processed / known image's Hu-moments)and labels for it but where we have to give the Hu-moments i calculated for current image?
you are trying to predict() the class for a current Hu-moment now ?
yes. whether i have to give its values as Mat to pedict( ) function? @berak
yes, do so, please.
Like @berak said is completely correct :)
I tried to write the coding but i stuck with two doubts i have hue moments for 5 data sets. two negative data hue moments. 1. how can i get the 7 data values in a program? 2.. How can i train the SVM with 7 data sets?