Signature Fraud Detection using Deep Learning | Python Final Year IEEE Project 2023
Signature Fraud Detection using Deep Learning | Python Final Year IEEE Project 2023 - 2024.
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📌IEEE Base Paper Title: Offline Handwritten Signature Verification using Image Processing Techniques.
🔬Our Proposed Project Title: Signature Fraud Detection using Deep Learning.
💡Implementation Code: PYTHON.
🔬Algorithm / Model Used: Siamese Neural Networks.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.5000/.
IEEE Base paper Abstract:
The use of signatures for personal identification and verification is quite common. Signatures are validated for many documents such as Bank cheques and legal transactions. The necessity for effective automated solutions for signature verification has grown as signatures are now a prerequisite for both authorization and authentication in legal activities. Two images—the original signature and the test signature—are used as input in this process. Prior to feature extraction, these photos are pre-processed. To determine whether the signature is fake or not, the characteristics that were extracted are compared, and the difference in error values between them is examined. The key advantages of signature verification systems (SVS) over alternative verification technologies include time and energy savings, a reduction in the risk of fraud during authentication, and a reduction in the likelihood of human error during the signature process.
REFERENCE:
V. Hindumathi; Jennifer Chalichemala; Endla Ameya; Vatadi Kavya Sri; Bhople Vaibhavi, “Offline Handwritten Signature Verification using Image Processing Techniques”, 2023 IEEE 8th International Conference for Convergence in Technology (I2CT), IEEE Conference, 2023.
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