# Otsu Thresholding : Why 'minimum within class variance' gives the optimum threshold?

I was trying to understand the Otsu thresholding algorithm in image processing. For that purpose I found a useful link. I got the algorithm flow, but a fundamental doubt arises. Why 'minimum within class variance' ${\sigma_W}^2$ (notation given in the link) gives the optimum threshold? Please can someone clear my doubt?