Advancing Security: Machine Learning-Based Signature Forgery Detection in Document Authentication Systems

Author(s)	Sandesh Kandel
Country	India
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
Published On	2023-11-18
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
DOI	https://doi.org/10.36948/ijfmr.2023.v05i06.9039
Short DOI	https://doi.org/gs5mgp

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