Publiora

Menghubungkan ke Publiora...

Publiora

Identification of Signature Images with Edge Detection Canny

Tasri, Yanti Desnita
Journal of Ocean, Mechanical and Aerospace -science and engineering- (Sinta 3)Vol. 0 No. 030 November 2022
DOI10.36842/jomase.v66i3.316

Abstrak

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.

Cari jurnal yang tepat untuk naskah Anda

MatchMind AI mencocokkan abstrak naskah Anda dengan ribuan jurnal terakreditasi dan menampilkan rekomendasi terbaik beserta alasannya.

Coba MatchMind

Lihat profil lengkap jurnal ini

Waktu review, biaya APC, statistik sitasi, indeksasi Scopus, dan banyak lagi.

Buka Journal of Ocean, Mechanical and Aerospace -science and engineering-

Artikel ini juga tersedia di situs resmi jurnal.

Identification of Signature Images with Edge Detection Canny | Journal of Ocean, Mechanical and Aerospace -science and engineering- | Publiora