A biometric-based verification system for handwritten image-based signatures using audio to image matching

Signing a document or a cheque by hand or using a stored image-based signature is known to be a valid method for authentication and authorisation by the signer. However, signature forging has advanced to replicate exactly how a signature looks, which can be done by skilfully, unskilfully or randomly forging a signature. Such a dilemma presents a challenge to accurately authenticate and authorise using signatures. In this study, a verification system is proposed for handwritten image-based signatures for validating whether the image-based signature is authentic rather than forged. The system maps the live stream of an audio-based signature with the investigated image-based signature and returns the match results. Matching is done by classification and/or by correlation between the two signatures. If matching shows a similar class or a score above a pre-defined threshold, the image-based signature is verified to be authentic, otherwise it is flagged as forged. A total of 20 participated in the experiment, where each participant provided a legitimate signature and forged four other signatures in different settings. In a double-blind setting, the system reported 95% accuracy using a one-class SVM and 100% accuracy using a correlation coefficient for detecting forged versus legitimate signatures.