International Journal For Multidisciplinary Research
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 5 Issue 6
Advancing Security: Machine Learning-Based Signature Forgery Detection in Document Authentication Systems
|Abstract||Handwritten signatures play a vital role in our lives. From banks to institutions to organizations, signatures are a way of identifying a person. However, signings come with a lot challenges because any two signatures can look very similar with slight differences written the same person. Therefore, the identification of real and fake signatures is very difficult. To avoid similar identity related crimes committed in banks and many others companies, the counterfeit detection system is the solution to this problem along with the help concepts of machine learning and CNN. For better performance and time efficiency, Parallelization concepts are used in software implementation. This software can be used to verify signatures on many platforms such as loans, signing legal documents, applications signing, applications and much more.|
|Keywords||crucial, banks, organization, forgery, CNN, forgery, signature, frauds.|
|Field||Computer > Data / Information|
|Published In||Volume 5, Issue 6, November-December 2023|
|Cite This||Advancing Security: Machine Learning-Based Signature Forgery Detection in Document Authentication Systems - Sandesh Kandel - IJFMR Volume 5, Issue 6, November-December 2023. DOI 10.36948/ijfmr.2023.v05i06.9039|
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