Work

Signature Verification Using The K-Nearest Neighbor (KNN) Algorithm and Using the Harris Corner Detector Feature Extraction Method

Year: 2022

Type: article

Abstract: The security of the transaction process is very important in this day and age. Signatures can be used as a means of guaranteeing the security of a transaction other than fingerprints. However, the threat of signature forgery for those who use signatures as security is still very high and frequent. In this research, we will verify the authenticity of a signature and test it using the K-Nearest Neighbour (KNN) algorithm and the Harris Corner feature extraction method. There are two kinds of distance calculations that will be used in the K-NN algorithm, namely by calculating the distance from Euclidean Distance and Manhattan Distance. The k value at KNN taken is at k = 1, k = 3, and k = 5.

Source: Buana Information Technology and Computer Sciences (BIT and CS)

DOI: 10.36805/bit-cs.v3i2.2763

Authors: Aang Alim Murtopo, Bayu Priyatna, Rini Mayasari

Institutions: Universitas Buana Perjuangan Karawang, University of Singaperbangsa Karawang

Language: English

Topic: Handwritten Text Recognition Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4312755656

FWCI: 0.416

Cites: 2

Cited by: 6

Related to: 10