Train SVM with OpenCV using colour histograms

Question

I'm very new to OpenCV, and i want to create simple object detector, that uses SVM. Instead of HOG, i would like to extract from my object color histograms(for example), but i couldn't find any information about it for OpenCV, everywhere is using HOG.

And my second question: is Python implemenation for SVM has less functionality than C++ (both for OpenCV) ?

Answer 1

You can use the OpenCV function calcHist to compute histograms.

calcHist(&bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histSize, &histRange, uniform, accumulate );

where,

• &bgr_planes[0]: The source array(s)
• 1: The number of source arrays
• 0: The channel (dim) to be measured. In this case it is just the intensity so we just write 0.
• Mat(): A mask to be used on the source array
• b_hist: The Mat object where the histogram will be stored
• 1: The histogram dimensionality.
• histSize: The number of bins per each used dimension
• histRange: The range of values to be measured per each dimension uniform and accumulate

Refer to the docs for more information.

You can also look at this answer which discusses C++ OpenCV SVM implementation and this answer which discusses Python OpenCV SVM implementation to get started.