A biometric‐based verification system for handwritten image‐based signatures using audio to image matching - Abdulaziz Almehmadi (IET Biometrics, 2022)
Abstract 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.