Signature Verification System by using Convolutional Neural Network (CNN)

Authors: Vipin Koshe, Ashwin Kadawey, Nikita Parihar, Yash Solanki, Pratik Pawar, Prof. Sonali Rathore

Country: India

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Abstract: One of the most popular verification biometrics is the signature[2], which uses handwritten signatures in cheques, applications, letters, forms, minutes, etc. A person's handwritten signature must be individually identified because each individual's signature is unique by nature. Verifying signatures is a popular technique for verifying someone while they are away. Human verification can be inaccurate and occasionally unsure. The most common method for confirming a person or a private is with a signature. A person's signature is used to identify them in all social, professional, and commercial contexts[2]. The word "signature verification" is extremely important because it could be misused and lead to significant losses. The signature may be a behavioral biometric trait that combines the signer's neuromotor characteristics (e.g., how our brain and muscles, among other things, shape how we tend to sign) as well as sociocultural influences (e.g., the differences between Western and Asian styles). Through the ages, United Nations agency experts have constructed signature examinations to verify the validity of sample-supported rhetorical analysis.

Keywords: CNN (Convolutional Neural Network), Signature Verification, Support Vector Machine, Biometric Analysis.[1]

Paper Id: 232312

Published On: 2025-03-23

Published In: Volume 13, Issue 2, March-April 2025

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