A survey for handwritten signature verification

Sanmorino, Ahmad; Yazid, Setiadi

doi:10.1109/urke.2012.6319582

Cited by 32 publications

(27 citation statements)

References 11 publications

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“…Literature further recommends the utilization of the Crossover Error Rate (CER) in addition to the previously discussed metrics [200]. This parameter is defined as the probability of the system being in a state where FAR equals to FRR.…”

Section: Robustness To Operating Environmentmentioning

confidence: 99%

Multi-Factor Authentication: A Survey

et al. 2018

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Today, digitalization decisively penetrates all the sides of the modern society. One of the key enablers to maintain this process secure is authentication. It covers many different areas of a hyper-connected world, including online payments, communications, access right management, etc. This work sheds light on the evolution of authentication systems towards Multi-Factor Authentication (MFA) starting from Single-Factor Authentication (SFA) and through Two-Factor Authentication (2FA). Particularly, MFA is expected to be utilized for human-to-everything interactions by enabling fast, user-friendly, and reliable authentication when accessing a service. This paper surveys the already available and emerging sensors (factor providers) that allow for authenticating a user with the system directly or by involving the cloud. The corresponding challenges from the user as well as the service provider perspective are also reviewed. The MFA system based on reversed Lagrange polynomial within Shamir's Secret Sharing (SSS) scheme is further proposed to enable more flexible authentication. This solution covers the cases of authenticating the user even if some of the factors are mismatched or absent. Our framework allows for qualifying the missing factors by authenticating the user without disclosing sensitive biometric data to the verification entity. Finally, a vision of the future trends in MFA is discussed.

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Section: Robustness To Operating Environmentmentioning

confidence: 99%

Multi-Factor Authentication: A Survey

et al. 2018

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“…Berdasarkan cara mendapatkan citra (akuisisi citra), verifikasi tanda tangan dapat dibagi menjadi dua kategori yaitu: online signature verfication dan offline signature verification [8]. Pada penelitian ini, Pada tahap ini dilakukan pemindaian terhadap kertas tanda tangan sehingga didapatkan citra digital dari tanda tangan.…”

Section: A Image Acquisition/akusisi Citra Tanda Tanganunclassified

Verifikasi Tanda Tangan Asli Atau Palsu Berdasarkan Sifat Keacakan (Entropi)

Arifin

Naf’an

2017

INFOTEL

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Abstrak -Tanda tangan merupakan penanda atau identitas yang ada pada suatu dokumen. Tanda tangan mempunyai peranan penting dalam memverifikasi dan melegalisasi dokumen. Tujuan dari penelitian ini menerapkan teknik pengolahan citra pada tanda tangan dan mengidentifikasi pola citra tanda tangan berdasarkan nilai entropi dan waktu perhitungan nilai entropi. Tahapan penelitian meliputi pengambilan data responden berupa tanda tangan citra analog, berikutnya akusisi citra tanda tangan digital dengan cara memindai tanda tangan tersebut, tahap selanjutnya mengkonversi citra tangan tangan digital dari true color menjadi binary. Tahap akhir melakukan perhitungan nilai entropi dan mencatat waktu perhitungan nilai entropi dengan menggunakan software matlab dan dilihat sebaran nilai entropi dari masing -masing citra tanda tangan. Sebaran nilai entropi pada tanda tangan asli mempunyai error 3,31% dari total responden (30 responden). Nilai error ini merupakan nilai entropi yang keluar dari kelompoknya. Waktu perhitungan nilai entropi pada tanda tangan palsu jika coretan atau piksel pada citra lebih besar dari citra tanda tangan asli maka waktu perhitungan nilai entropinya lebih lama dibandingkan dengan citra tanda tangan asli.Kata kunci -Tanda Tangan, Konversi citra digital, Nilai Entropi.Abstract -Signature is a token or an identity that exists on a document. Signature has an important role in the verification and legalization of a document. The purpose of this research is to apply image processing technique on signatures and to classify their patterns based on entropy values and time calculation entropy value. Stages of this research include the retrieval of respondent data in the form of signature's analog images, followed by the acquisition of digital signature images by way of scanning them and the next stage is to convert digital signature images from true color to binary. The last stage is to calculate entropy values and time calculation entropy value by using Matlab software and entropy value distribution of every signature is then reviewed. Distribution of entropy values in the original signature has an error of 3.31% out of the total respondents (30 respondents). This error value is the value of entropy that falls outside of the group. If the strokes or pixels on a forged signature are larger than those of original one then the computation time to process the forged signature will be longer than it took to process the original one.

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“…Besides these surveys, special survey were published in the past few years, such as the verification survey by Sanmorino et al [5], and papers on online signature verification, by Zhang et al [6] and El-Henawy et al [7].…”

Section: Related Workmentioning

confidence: 99%

Online Signature Verification Based on Kolmogorov-Smirnov Distribution Distance

Griechisch

Malik

Liwicki

2014

2014 14th International Conference on Frontiers in Handwriting Recognition

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Online signature verification methods examine the dynamics of the handwriting process to decide whether a signature is probably genuine or forged. Most of the previously proposed methods for online signature verification apply Neural Networks, Dynamic Time Warping, or Hidden Markov Model for classification and they consider several aspects, like planar coordinates, pressure, velocity, and acceleration with respect to time. Here we apply a non-parametric statistical test for a comparison of features and the verification of signatures.

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A survey for handwritten signature verification

Cited by 32 publications

References 11 publications

Multi-Factor Authentication: A Survey

Multi-Factor Authentication: A Survey

Verifikasi Tanda Tangan Asli Atau Palsu Berdasarkan Sifat Keacakan (Entropi)

Online Signature Verification Based on Kolmogorov-Smirnov Distribution Distance

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