# Using Principal Component Analysis for corner feature extraction

I am on a project of vehicle type Identification (MUV,jeep,Sedan,etc) from images and Here is what I have done up-to now on matlab.

I am working only on the sideview of images.

Then I detected the corners easily

Now I got a matrix C with 40 corner coordinates thus I got a matrix of C=[40x2]
I converted it to a linear form using C=C(:); so I got C=[1x80] (as Neural Network destroys coordinates information itself) for 1 image
But I have about 9 image for each class(MUV,Jeep,Sedan) so I made a matrix using C matrix to form a new matrix say MAT=[9x80]

Now I have a corner feature of MAT=[9x80]
1. What Other features could I use or the corner feature would itself be fine enough.(may be SURF features)
2. The Input Format of NN is inMAT=[nxm] where n=number of features and m=total images and target Format is tgMAT=[cxm] where c=number of classes (MUV,Sedan,jeep) and 'm=total images'. Am I right here?

• Why do you think this would work? I mean, PCA essentially works if you give it high-dimensional data that's a linear combination of a few vectors (the principal components). I don't see why corner coordinates in more or less random order would be combinations of a few linear components. – Niki Estner Nov 9 '13 at 10:34
• Ok so Can I use the Corner vector MAT=[9x80] features directly as a feature vector for training and classification? – noobmaster69 Nov 9 '13 at 11:44
• @nikie I have made some edits to question please check it – noobmaster69 Nov 9 '13 at 12:18
• I think 9 samples are not enough to train. You can also try polar coordinates in some cases they give better results. You can also use bounding box sizes of the cars as input. But mainly you should decide the type of input you want to use vectorel (require a lot of pre processing) or image information. You can check pattern recognition and character recognition steps for image information usage in NNs. – s.s.o Nov 12 '13 at 11:40

• Also I am asking it here because I know you guys are practical in this field and when I ask my professor/mentor about any help then all I see is a Confused face saying Ok I will see it...!! You may leave now – noobmaster69 Nov 9 '13 at 14:50