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Relevant bibliographies by topics / Handwritten Signature Verification / Dissertations / Theses

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Dissertations / Theses on the topic 'Handwritten Signature Verification'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

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1

Sindle, Colin. "Handwritten signature verification using hidden Markov models." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53445.

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Thesis (MScEng)--University of Stellenbosch, 2003.<br>ENGLISH ABSTRACT: Handwritten signatures are provided extensively to verify identity for all types of transactions and documents. However, they are very rarely actually verified. This is because of the high cost of training and employing enough human operators (who are still fallible) to cope with the demand. They are a very well known, yet under-utilised biometric currently performing far below their potential. We present an on-line/dynamic handwritten signature verification system based on Hidden Markov Models, that far out performs

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2

Le, Riche Pierre (Pierre Jacques). "Handwritten signature verification : a hidden Markov model approach." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51784.

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Thesis (MEng)--University of Stellenbosch, 2000.<br>ENGLISH ABSTRACT: Handwritten signature verification (HSV) is the process through which handwritten signatures are analysed in an attempt to determine whether the person who made the signature is who he claims to be. Banks and other financial institutions lose billions of rands annually to cheque fraud and other crimes that are preventable with the aid of good signature verification techniques. Unfortunately, the volume of cheques that are processed precludes a thorough HSV process done in the traditional manner by human operators. It

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3

Amsbury, Burl. "Core technology through enterprise launch : a case study of handwritten signature verification." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/88338.

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4

Shashidhar, Sanda, and Amirisetti Sravya. "Online Handwritten Signature Verification System : using Gaussian Mixture Model and Longest Common Sub-Sequences." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15807.

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5

McCormack, Daniel Keith Raymond. "An investigation into the representation of data for the neural implementation of a handwritten static signature verification system." Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338970.

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6

Olander, Sahlén Simon. "Feature Analysis in Online Signature Verification on Digital Whiteboard : An analysis on the performance of handwritten signature authentication using local and global features with Hidden Markov models." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-224661.

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The usage of signatures for authentication is widely accepted, and remains one of the most familiar biometric in our society. Efforts to digitalise and automate the verification of these signatures are hot topics in the field of Machine Learning, and a plethora of different tools and methods have been developed and adapted for this purpose. The intention of this report is to study the authentication of handwritten signatures on digital whiteboards, and how to most effectively set up a dual verification system based on Hidden Markov models (HMMs) and global aggregate features such as average sp

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7

Fang, Bin, and 房斌. "Verification of off-line handwritten signatures." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31241645.

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8

Kaplani, Eleni. "Human and computer-based verification of handwritten signatures." Thesis, University of Kent, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.396378.

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9

Qi, Yingyong. "A multiresolution approach to computer verification of handwritten signatures." Diss., The University of Arizona, 1993. http://hdl.handle.net/10150/186548.

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This dissertation presents procedures and results of works on computer signature verification. Two methods were developed and evaluated. First, verification was made using multi-resolution feature representation. This multi-resolution feature representation included global geometric characteristics and wavelet transformations of a signature image. A number of algorithms were developed to extract the global geometric features. A vector quantization classifier and a neural-network classifier were designed to use the multi-resolution representation for verification. Second, verification was made

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10

Lo, Wei-Hsien, and 羅尉賢. "Video-based Handwritten Signature Verification." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/68968926979823245638.

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碩士<br>國立中央大學<br>資訊工程研究所<br>98<br>This paper proposes a video-based handwritten signature verification framework. When acquiring signature information, we use a webcam in substitution for a digitizing tablet. Because webcams are more prevalent and cheaper than digitizing tablets, using webcams as sensors can reduce the cost. In addition, the features extracted using a webcam also contain more information. In tradition handwritten signature verification, features extracted using a digitizing tablet are mainly trajectories. But for the features extracted using a webcam, we can acquire pen graspin

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11

Huang, Ying-Hao, and 黃英豪. "Handwritten Signature Verification System using Neural Network." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/60130490678407077969.

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碩士<br>明道大學<br>管理研究所<br>96<br>In recent years, there are many ways to verify personal identity. Traditional methods is using password. However, it might be forgotten, lost, or stolen. To prevent occurring these uncomfortable situations, biometrical verifying identity methods is proposed. There are two categories. First method is physiological verification (e.g. face, fingerprints, iris, and hand). The other is behavioral verification (e.g. signature verification, speech, and walk speed. Recent researches show that signature verification system is welcome by most people. In this study, I use WAC

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12

McCabe, Alan. "Handwritten signature verification using complementary statistical models." Thesis, 2003. https://researchonline.jcu.edu.au/1246/1/01front.pdf.

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There is considerable interest in computerised personal identification and in particular in biometrics, a branch of identification that deals with verifying physical or behavioural characteristics of human beings. This thesis is concerned with the development of the particular biometric of handwritten signature verification which is superior in many ways to other biometric authentication techniques that may be reliable but are much more intrusive. Specifically this project involves the use of two complementary artificially intelligent systems in the form of neural networks and hidden Markov mo

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13

McCabe, Alan. "Handwritten signature verification using complementary statistical models /." 2003. http://eprints.jcu.edu.au/1246.

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14

Hung-Yu, Cheng, and 鄭弘裕. "Verification of Handwritten Signature with Any Rotation Angle." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/51984599983749288503.

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15

Moolla, Yaseen. "Handwritten signature verification using locally optimized distance-based classification." Thesis, 2012. http://hdl.handle.net/10413/10112.

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Although handwritten signature verification has been extensively researched, it has not achieved optimum accuracy rate. Therefore, efficient and accurate signature verification techniques are required since signatures are still widely used as a means of personal verification. This research work presents efficient distance-based classification techniques as an alternative to supervised learning classification techniques (SLTs). Two different feature extraction techniques were used, namely the Enhanced Modified Direction Feature (EMDF) and the Local Directional Pattern feature (LDP). These were

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16

Tzu-Yan, Ho, and 何姿燕. "Online Handwritten Signature Verification System-Based On Bayesian Classifier." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/39927286343109565372.

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碩士<br>國立新竹教育大學<br>資訊科學研究所<br>98<br>The biometric is widespread used for recognizing the identification. The popular methods for identification, for example, fingerprints, iris, voice and so on, need to collect personal biometric information. However, with the rising awareness of human rights and privacy issues, researches must face the trade-off between the recognition rate and privacy. This study proposed a system which records each signature and analyzes the characteristic of personal handwriting. Most of the on-line and off-line handwriting signatures were recorded in digital format at firs

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17

Ling, Yu-Siang, and 凌于翔. "Three-Dimensional Chinese Handwritten Signature Verification Using Biometric Characteristics." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/69217160196255840490.

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博士<br>國立中央大學<br>資訊工程學系<br>104<br>Signature Verification System has been widely used in several occasions that people need to provide their identities, including in government institution and in some business activities. Using handwritten signature as a biometric verification has lots of advantages, unlike passwords, passwords could be forgotten or embezzled. Also, it has lower cost than traditional biometric verification, such as iris, face, and finger print, which need expensive hardware equipment to capture images information. We can acquire handwritten signature just through a digitizer or

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18

Deng, Peter Shaohua, and 鄧少華. "Biometric-based Pattern Recognition -- Handwritten Signature Verification and Face Recognition." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/79526579531096548003.

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博士<br>國立中央大學<br>資訊工程研究所<br>88<br>In this dissertation, two biometric-based pattern recognition problems were studied, i.e., off-line handwritten signature verification and human face recognition. Biometrics, by definition, is the automated technique of measuring a physical characteristic or person trait of an individual and comparing the characteristic or trait to a database for purposes of recognizing or authenticating that individual. Biometrics uses physical characteristics, defined as the things we are, and personal traits, defined as the things we behave, including facial thermographs, c

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19

Lee, Hao-Wei, and 李晧暐. "MOBILE DEVICE HANDWRITTEN SIGNATURE VERIFICATION BASED ON MODIFIED FACET ANALYSIS METHOD." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/mjkmyd.

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碩士<br>大同大學<br>資訊經營學系(所)<br>102<br>This paper proposed a method for signature verification and made experiments on mobile devices. In the application of online signing such as shopping with credit cards, real-time verification is imperative to prevent forgeries. When we open an account in a financial institution, we need to sign our names several times in various forms that can be used as a basis for extracting features for future comparison. Dynamic attribute values such as XY-coordinates, T(time duration) and P(pen pressure) are collected. Based on the modified Facet Analysis Method, we are a

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20

Tsai, Ming-Ying, and 蔡銘穎. "Handwritten Signature Verification System Based on Wavelet Transform and Machine Learning." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/dkfnwv.

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碩士<br>國立臺灣大學<br>電信工程學研究所<br>105<br>In the past couple of decades, techniques for handwritten signature verification have been thoroughly studied and put into practice in various systems, which include security systems and financial field where credit cards verification is much needed. Generally speaking, handwritten signature verification system can be categorized into two kinds, online and offline verification. The former requires stylus pens and tablet computers to capture dynamic signature information, whilst for offline verification, a scanner is used to turn handwritten information into s

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21

Chen, Yi-Chi, and 陳翌綺. "A Handwritten Signature Verification System Based on G-sensor and Gyroscope." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/pjw8tc.

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碩士<br>國立交通大學<br>資訊科學與工程研究所<br>105<br>In this thesis, through a variety of signal processing methods in research and analysis, accelerometer and gyroscope were used to implement a signature recognition system at the aim of identity authentication. Classified by recognition of selfsignature and counterfeit signatures, three modes are considered, including longtime analysis and testing of self-signature by identity, forged signature by counterfeiters with continuous practicing or directly through tracing paper. The average recognition rate can reach up to 93.47%. In the presented method, an indep

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22

Kao, Chienchih, and 高健智. "Handwritten Signature Verification and the S&P 500 Index Forecasting by Artificial Neural Network." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/32922463160735521984.

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碩士<br>國立高雄海洋科技大學<br>電訊工程研究所<br>100<br>Handwritten signature verification system use personal signature as a recognizing tool, which records signature and analyzes person’s handwriting, according to different personal handwritten way. To form the complete handwritten signature verification system, Probabilistic Neural Network, image preprocess, and feature analysis technology were used in this research. The database of this system was consisted of 20 people’s personal handwriting; use image process technology to decrease the variability which might influence the classification, and analyze the

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