If the details of the "hashing" scheme used is publicized, I imagine it will be near trivial. It's a long-standing problem in computer vision, to find a digital description of an image such that two similar images compare equal or at least similar.

State-of-the-art for this field is deep learning, and a /huge/ problem with the DL approach is that you can generate adversarial examples. So for example, a picture of a teacup that is identified by /most/ networks as a dog. It's particularly damning, because it seems like you don't have to do this for particular deep networks, they get tricked the same way, so to speak.