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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM18046
Volume:
7 |
3 |
Mar 2023
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Even though most areas, including land records, agreements between parties, legal certificates, identification cards, etc., are moving toward digital documents with digital signatures for authentication, uses only a signature written by hand. Verifying signatures is crucial because a false signature would have a significant impact on the actual owner. Therefore, it is essential to recognize genuine signatures in order to avoid such frauds. In this work, the deep learning technique is used to recognize the signature because it produces the highest accuracy and does not require excessive preprocessing. Image processing, classification, and segmentation are the most common applications for a deep learning model that is based on a convolutional neural network (CNN). The CNN algorithm learns more than KNN, SVM, and other algorithms. This work makes use of CNN to improve classification.
KEYWORDS
Publication Date
5/25/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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