Learning Features for Offline Handwritten Signature Verification using Deep Convolutional Neural Networks.

•We propose formulations for learning features for Offline Signature Verification.•A novel method that uses knowledge of forgeries from a subset of users is proposed.•Learned features are used to train classifiers for other users (without forgeries).•Experiments on GPDS-960 show a large improvement in state-of-the-art.•Results in other 3 datasets show that the features generalize without fine-tuning.