A technique for estimating handwritten signature complexity based on human perceptual criteria

Eleni Kaplani; Michael C. Fairhurst

A technique for estimating handwritten signature complexity based on human perceptual criteria

Eleni Kaplani
, Michael C. Fairhurst

Sustainable Energy

Research output: Contribution to conference › Poster › peer-review

Abstract

In spite of the numerous algorithms for automating the verification of handwritten signatures that have been proposed over the years, there are still many handwritten signatures that can cause a system to underperform significantly. Two main elements are responsible for this: the variability of a signature and its complexity. Studies reported analyse these elements in much detail, and include an estimation of a signature's complexity in terms of the difficulty that a potential forger would encounter in an attempt to reproduce it dynamically. This paper introduces a technique to estimate the complexity of a signature image based on knowledge acquired from a human experiment, where 'complexity' is viewed from a different perspective. Importantly, the measure we propose is based entirely on the static signature image.

Original language	English
Number of pages	2
Publication status	Published - 2002

Cite this

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title = "A technique for estimating handwritten signature complexity based on human perceptual criteria",

abstract = "In spite of the numerous algorithms for automating the verification of handwritten signatures that have been proposed over the years, there are still many handwritten signatures that can cause a system to underperform significantly. Two main elements are responsible for this: the variability of a signature and its complexity. Studies reported analyse these elements in much detail, and include an estimation of a signature's complexity in terms of the difficulty that a potential forger would encounter in an attempt to reproduce it dynamically. This paper introduces a technique to estimate the complexity of a signature image based on knowledge acquired from a human experiment, where 'complexity' is viewed from a different perspective. Importantly, the measure we propose is based entirely on the static signature image.",

author = "Eleni Kaplani and Fairhurst, \{Michael C.\}",

note = "Proc. PREP 2002 International Conference, Nottingham, UK",

year = "2002",

language = "English",

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TY - CONF

T1 - A technique for estimating handwritten signature complexity based on human perceptual criteria

AU - Kaplani, Eleni

AU - Fairhurst, Michael C.

N1 - Proc. PREP 2002 International Conference, Nottingham, UK

PY - 2002

Y1 - 2002

N2 - In spite of the numerous algorithms for automating the verification of handwritten signatures that have been proposed over the years, there are still many handwritten signatures that can cause a system to underperform significantly. Two main elements are responsible for this: the variability of a signature and its complexity. Studies reported analyse these elements in much detail, and include an estimation of a signature's complexity in terms of the difficulty that a potential forger would encounter in an attempt to reproduce it dynamically. This paper introduces a technique to estimate the complexity of a signature image based on knowledge acquired from a human experiment, where 'complexity' is viewed from a different perspective. Importantly, the measure we propose is based entirely on the static signature image.

AB - In spite of the numerous algorithms for automating the verification of handwritten signatures that have been proposed over the years, there are still many handwritten signatures that can cause a system to underperform significantly. Two main elements are responsible for this: the variability of a signature and its complexity. Studies reported analyse these elements in much detail, and include an estimation of a signature's complexity in terms of the difficulty that a potential forger would encounter in an attempt to reproduce it dynamically. This paper introduces a technique to estimate the complexity of a signature image based on knowledge acquired from a human experiment, where 'complexity' is viewed from a different perspective. Importantly, the measure we propose is based entirely on the static signature image.

M3 - Poster

ER -