Understanding Jump Flooding Algorithm (JFA) for Voronoi Diagrams
I think that there is a bit of confusion in terminology. My understanding is that only the initially colored points, before step 1, are called seeds. 

Maybe this helps clarify the algorithm as well. When the a point $ p $ with color $ s $ finds a neighbor $ q $ with color $ s' $, he compares the distance $ d(p,s) $ with $ d(p,s') $ (not $ d(p,q) $) to decide his new color. This is why each pixel crucially holds the $ (x,y) $ coordinates of his seed color (in the paper they used the r,g channels for this) and not just the distance. In each step this data is also passed to the neighbor. 

So in that example, in moving from step length 4 to step length 2, that red square (the circled one that remains red) sees the green square who tells red square that the green seed is at $ (8,6) $. Red square then computes his distance to green square to be $ \sqrt{2^2 + 4^2} $, which is bigger than the distance to red ($ 4 $), and so remains red.