In authenticating and verifying important documents, one of them is in the form of identifying the authenticity of a signature. In addition, the signature is also a form of ratification and a sign of approval in important documents is mandatory. Along with current technological developments, the signing process can be carried out in digital media such as cellphones and other media. The ability of the system to identify a person's signature becomes important because of the many forgeries that occur. This study aims to implement the Canny edge detection method to identify a person's signature. The number of signature images used is 10 signatures. The results of this study indicate that the Canny edge detection method has a similarity percentage of 70% to 100%, and the similarity values below 70% and above 100% are grouped into signature images that are not original.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.