Non-statistical methods of imitating handwriting are always fairly easy to identify as synthetic due to the uniformity of strokes and unnatural kerning (among other things). Even methods which incorporate random variations don't hide these artifacts sufficiently well. In my opinion, the only way to generate synthetic handwriting which is convincingly real is to use statistical methods (i.e. machine learning) to model all variation which is present in real handwriting. I've implemented a neural network in javascript which does exactly this - https://seanvasquez.com/handwriting-generation/. You can play around with it and find a few weaknesses, but in general I find that it can produce handwriting which is indistinguishable from real handwriting.