A biometric‐based verification system for handwritten image‐based signatures using audio to image matching
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...
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| Format: | Article |
| Language: | English |
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Wiley
2022-03-01
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| Series: | IET Biometrics |
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| Online Access: | https://doi.org/10.1049/bme2.12059 |
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| author | Abdulaziz Almehmadi |
| author_facet | Abdulaziz Almehmadi |
| author_sort | Abdulaziz Almehmadi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-b2e1c1e128c3470a8934d90b0e02d091 |
| institution | OA Journals |
| issn | 2047-4938 2047-4946 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Biometrics |
| spelling | doaj-art-b2e1c1e128c3470a8934d90b0e02d0912025-08-20T02:23:24ZengWileyIET Biometrics2047-49382047-49462022-03-0111212414010.1049/bme2.12059A biometric‐based verification system for handwritten image‐based signatures using audio to image matchingAbdulaziz Almehmadi0Department of IT Faculty of Computing and IT SNCS Research Center University of Tabuk Tabuk Saudi ArabiaAbstract 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.https://doi.org/10.1049/bme2.12059behavioural biometricsbiometric applicationshandwriting biometricshandwriting recognitionsignature biometrics |
| spellingShingle | Abdulaziz Almehmadi A biometric‐based verification system for handwritten image‐based signatures using audio to image matching IET Biometrics behavioural biometrics biometric applications handwriting biometrics handwriting recognition signature biometrics |
| title | A biometric‐based verification system for handwritten image‐based signatures using audio to image matching |
| title_full | A biometric‐based verification system for handwritten image‐based signatures using audio to image matching |
| title_fullStr | A biometric‐based verification system for handwritten image‐based signatures using audio to image matching |
| title_full_unstemmed | A biometric‐based verification system for handwritten image‐based signatures using audio to image matching |
| title_short | A biometric‐based verification system for handwritten image‐based signatures using audio to image matching |
| title_sort | biometric based verification system for handwritten image based signatures using audio to image matching |
| topic | behavioural biometrics biometric applications handwriting biometrics handwriting recognition signature biometrics |
| url | https://doi.org/10.1049/bme2.12059 |
| work_keys_str_mv | AT abdulazizalmehmadi abiometricbasedverificationsystemforhandwrittenimagebasedsignaturesusingaudiotoimagematching AT abdulazizalmehmadi biometricbasedverificationsystemforhandwrittenimagebasedsignaturesusingaudiotoimagematching |