Face hashing is different than generic image hashing. Methods like dividing the photo into smaller rectangles and storing the average colour for each rectangle won't work.
It should be able to detect and hash facial features so that it can compare it to a future (potentially taken from a different angle) photo of the same person. You need some type of machine learning algorithm.
yes, I've worked on face recognition databases with 150m and 40m faces for banking and safety.
The models are not perfect. Humans should still be in the loop to verify, especially when the consequences of being wrong really suck for the user: losing access to their bank account, getting fired from their job.
If you're referring to algorithms like phash (Where they are using the same core image, but just add a filter), they wont work well, because everyone's ID card mostly looks the same. There will be too many FPs.
To be honest, I don't understand what exactly is the problem that needs to be solved. Two people using the same image? Two people using the same ID? The same person registering two accounts using two different IDs but they're both a photo of the same person?
