CODEWITHSUNDEEP
c++opencvimage-processing
AkJ
AkJ

Reputation: 73

Training SVM with images of different dimensions

I'm trying to implement automatic number plate detection (ANPR). I'm using following tools.
- Ubuntu 12.04 OS
- OpenCV 2.4.13 with C++

I'm using some sample images, each having different dimensions to prepare the training dataset. Some image dimensions I'm using are as follows:
- 468 * 294
- 600 * 375
- 1024 * 776
etc.

I've gone through using OpenCV and SVM with images , and got the impression that this method would work if all the images are of same dimension. Also Training a classifier using images of different dimensions but same number of HoG features, I think this might also not be an accurate solution.

Is there some other way to train SVM with different image dimensions?

Upvotes: 2

Views: 1436

Answers (1)

Andrey Smorodov
Andrey Smorodov

Reputation: 10852

Usual practice is to resize input images before feeding them to classifier, because you have fixed number of inputs, you need fixed dimentionality of features, in your case features are pixel intensities, so, number of pixels in your input image must be fixed.

Upvotes: 2

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