Difference between cv2.NORM_L2 and cv2.NORM_L1 in opencv python

Question

I am using sift algorithm from python extra modules for some feature matching. Although one thing I did not understand is the concept behind the normType passed to the BFMatcher. i.e Which ones have to be used in what case?

Any help will be invaluable

Briefless

Answer 1

From WolframAlpha NormL1 and NormL2:

Given a vector:

Norm L1 is the taxicab (or manhattan) distance (sum of absolute values):

while Norm L2 is the euclidean distance (square root of sum of squares):

The type of norm tells the BFMatcher how to compute the distances between every two features.

The NORM L1 is in general much faster to compute (mostly because you don't compute the square root). The NORM L2 is more accurate.

You can find a nice comparison here.

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