DETECTION OF FORGERY IN HANDWRITTEN SIGNATURES

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DETECTION OF FORGERY IN HANDWRITTEN SIGNATURES

Monu Agrawal, Riwaz Udas, Pranav Kumar Jha

Abstract—In our life, handwritten signatures are essential. Signatures are used to identify people in organizations like banks and institutions. But there are several difficulties associated with signatures since even two written by the same individual may resemble one another very little. It becomes quite challenging to distinguish between authentic and fake signatures as a result. Forgery detection systems, in conjunction with the ideas of machine learning and CNN, are a solution to this issue to prevent any such identity frauds conducted in banks and many other businesses. The program is implemented using parallelization ideas for improved speed and time economy. This application may be used to verify signatures on a variety of platforms, including applying for loans, signing legal documents, applications, and much more.

Index Terms—parallelization, CNN, signatures, authentic

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