IJEBM | Offline Signature Recognition and It’s Forgery Detection using Machine Learning Technique

Indexing and Abstracting

Offline Signature Recognition and It’s Forgery Detection using Machine Learning Technique

Malay Karmakar

International Journal of Engineering, Business And Management(IJEBM), Vol-7,Issue-2, March - April 2023, Pages 1-5 , 10.22161/ijebm.7.2.1

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Article Info: Received: 25 Jan 2023; Received in revised form: 25 Feb 2023; Accepted: 05 Mar 2023; Available online: 13 Mar 2023

Abstract:

Signature verification is an important aspect in today’s World. Signature has been verified in Banks, Government Agencies, Universities (Degree Verification) etc. Signature can involve in its shape, size, pressure, speed and angle. From a population of Signatures an original signature can be found out and distinguished. In this Paper for Forgery signature Detection we use two algorithm viz.Harris Algorithm and Surf Algorithm. We have also discussed about CNN Algorithm. Moreover in this paper we take the x-y co-ordinate of the real signature and also the x-y co-ordinate of the forged signature and compare among the two. We have used Python Programming for plotting the graphs whereas the graph can be plot using Matlab, R, Microsoft Excel and Python.

Keywords:

Python, R, CNN Algorithm, Harris Algorithm, Surf Algorithm, Matlab, Microsoft ExcelReceived: 25 Jan 2023; Received in revised form: 25 Feb 2023; Accepted: 05 Mar 2023; Available online: 13 Mar 2023

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