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

Aang Alim Murtopo, B. Priyatna, Rini Mayasari
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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.
基于k -最近邻(KNN)算法和Harris角点检测器特征提取方法的签名验证
在这个时代,交易过程的安全性非常重要。除了指纹,签名还可以作为保证交易安全性的一种手段。然而,对于那些使用签名作为安全保障的人来说,签名伪造的威胁仍然是非常高和频繁的。在本研究中,我们将使用k近邻(KNN)算法和哈里斯角特征提取方法验证签名的真实性并对其进行测试。在K-NN算法中有两种距离计算,即计算到欧几里得距离和曼哈顿距离的距离。取KNN处的k值为k = 1, k = 3, k = 5。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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