A survey for handwritten signature verification

Ahmad Sanmorino; Setiadi Yazid

doi:10.1109/URKE.2012.6319582

A survey for handwritten signature verification

Ahmad Sanmorino, Setiadi Yazid

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

27 Citations (Scopus)

Abstract

Signature verification is the process used to recognize an individual's handwritten signature. Signature verification can be divided into two main areas depending on the data acquisition method, off-line and on-line signature verification. In this paper we attempt to survey the signature verification based on three categories. First, judging from how to get the data signature which is off-line and on-line verification. Second, based on the technique used, that is rule-based approach, neural networks, hidden markov model and support vector machine. Third, based on preprocessing and feature extraction, which is thinning and line segmentation. Based on the survey, it was concluded that any method of verification has advantages and disadvantages. However, if viewed from the ease of implementation and performance, using neural networks or hidden markov models are the right choice. Depending on the data acquisition method, on-line verification is recommended to use than off-line verification.

Original language	English
Title of host publication	Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012
Pages	54-57
Number of pages	4
DOIs	https://doi.org/10.1109/URKE.2012.6319582
Publication status	Published - 2012
Event	2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012 - Jakarta, Indonesia Duration: 14 Aug 2012 → 15 Aug 2012

Publication series

Name	Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012

Conference

Conference	2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012
Country/Territory	Indonesia
City	Jakarta
Period	14/08/12 → 15/08/12

Keywords

Handwritten Signature
Hidden Markov Model
Line Segmentation
Neural Networks
Off-line Verification
On-line Verification
Rule-Based
Support Vector Machine
Thinning
Verification

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10.1109/URKE.2012.6319582

Cite this

Sanmorino, A., & Yazid, S. (2012). A survey for handwritten signature verification. In Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012 (pp. 54-57). Article 6319582 (Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012). https://doi.org/10.1109/URKE.2012.6319582

@inproceedings{382e11eea7874e218bd283f5bb015b11,

title = "A survey for handwritten signature verification",

abstract = "Signature verification is the process used to recognize an individual's handwritten signature. Signature verification can be divided into two main areas depending on the data acquisition method, off-line and on-line signature verification. In this paper we attempt to survey the signature verification based on three categories. First, judging from how to get the data signature which is off-line and on-line verification. Second, based on the technique used, that is rule-based approach, neural networks, hidden markov model and support vector machine. Third, based on preprocessing and feature extraction, which is thinning and line segmentation. Based on the survey, it was concluded that any method of verification has advantages and disadvantages. However, if viewed from the ease of implementation and performance, using neural networks or hidden markov models are the right choice. Depending on the data acquisition method, on-line verification is recommended to use than off-line verification.",

keywords = "Handwritten Signature, Hidden Markov Model, Line Segmentation, Neural Networks, Off-line Verification, On-line Verification, Rule-Based, Support Vector Machine, Thinning, Verification",

author = "Ahmad Sanmorino and Setiadi Yazid",

year = "2012",

doi = "10.1109/URKE.2012.6319582",

language = "English",

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pages = "54--57",

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note = "2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012 ; Conference date: 14-08-2012 Through 15-08-2012",

}

Sanmorino, A & Yazid, S 2012, A survey for handwritten signature verification. in Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012., 6319582, Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012, pp. 54-57, 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012, Jakarta, Indonesia, 14/08/12. https://doi.org/10.1109/URKE.2012.6319582

A survey for handwritten signature verification. / Sanmorino, Ahmad; Yazid, Setiadi.
Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012. 2012. p. 54-57 6319582 (Proceeding of 2012 International Conference on Uncertainty Reasoning and Knowledge Engineering, URKE 2012).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - Signature verification is the process used to recognize an individual's handwritten signature. Signature verification can be divided into two main areas depending on the data acquisition method, off-line and on-line signature verification. In this paper we attempt to survey the signature verification based on three categories. First, judging from how to get the data signature which is off-line and on-line verification. Second, based on the technique used, that is rule-based approach, neural networks, hidden markov model and support vector machine. Third, based on preprocessing and feature extraction, which is thinning and line segmentation. Based on the survey, it was concluded that any method of verification has advantages and disadvantages. However, if viewed from the ease of implementation and performance, using neural networks or hidden markov models are the right choice. Depending on the data acquisition method, on-line verification is recommended to use than off-line verification.

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A survey for handwritten signature verification

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Keywords

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