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What are the real world implications of this project?. Signatures are used to verify a person is who they say they are. Things like credit cards, checks use signatures to verify id. Things like contracts use a signature to the contract legally binding.
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What are the real world implications of this project? Signatures are used to verify a person is who they say they are. Things like credit cards, checks use signatures to verify id Things like contracts use a signature to the contract legally binding Finding forges could save banks and credit card companies lots of money
Gathering the Data First: Sign my name into a computer 100 times in a 2x6 inch image real Then: Have 2 other people sign their name once, sign my name 4 times and then try to forge my signature while looking at my signature as a guide real forged
Do Dimension Reduction on the Inputs This makes it so we have a reasonable amount of inputs
Run the Inputs on an MLP Found optimal parameters are Alpha = .01 Mom = .8 Epochs = 1000 Epoch size = 64 Checks every 10 Epochs With these parameters the MLP converges in < 300 Epochs !
Results Valid Signature If the data is trained with one persons forges and tested with the other persons forges worst case scenario it is classifies 22% of the samples incorrectly The MLP has lots of problems with this forged signature Forged Signature
Conclusion The MLP preformed quite well compared to both of the baseline models. If we look at real world scenarios, having absolutely no data on the forger, then the model was accurate 80-90% of the time. What makes these results useful is that the MLP was 100% accurate when claiming a signature was forged. This means that if someone were to implement this style in a bank to check for forged bank checks, if it ever flagged a signature as being forged, it would be a good idea to double check to see if is a valid transaction since the MLP appears not to give false positives in this scenario. The toughest part of this would be generating good forged signatures to test over. Other then having a person forge a signature several times for input, the MLP will not work. The good news is that if one can get this data, the MLP seems to work to detect forges signed by someone else.
