Dynamic Handwritten Signature Research Articles

Smartphone-based Handwritten Signature Verification using Acoustic Signals

Handwritten signature verification techniques, which can facilitate user authentication and enable secure information exchange, are still important in property safety. However, on-line automatic handwritten signature verification usually requires dynamic handwritten patterns captured by a special device, such as a sensor-instrumented pen, a tablet or a smartwatch on the dominant hand. This paper presents SonarSign, an on-line handwritten signature verification system based on inaudible acoustic signals. The key insight is to use acoustic signals to capture the dynamic handwritten signature patterns for verification. Particularly, SonarSign exploits the built-in speakers and microphones of smartphones to transmit a specially designed training sequence and record the corresponding echo for channel impulse response (CIR) estimation, respectively. Based on the sensitivity of CIR to the tiny surrounding environment changes including handwritten signature actions, SonarSign designs an attentional multi-modal Siamese network for end-to-end signatures verification. First, multi-modal CIR streams are fused to extract representative signature pattern features from spatio-temporal dimensions. Then an attentional Siamese network is elaborated to verify whether the given two signatures are from the same signatory. Extensive experiments in real-world scenarios show that SonarSign can achieve accurate and robust signatures verification with an AUC (Area Under ROC (Receiver Operating Characteristic) Curve) of 98.02% and an EER (Equal Error Rate) of 5.79% for unseen users.

Dynamic handwritten signature and machine learning based identity verification for keyless cryptocurrency transactions

In this paper we propose a novel system for identity verification by amalgamating online signature verification, machine learning, IOT and blockchain to garner their potentials to cope up and to contain this risk of identity theft specifically in the case of online transactions. In this system signals of roll, pitch and yaw values retrieved from MPU6050 sensor (Inertial Measurement Unit) are analysed using Digital Time Wrapping to obtain DTW minimum distance to verify the identity of the user. In case of cryptocurrencies, we propose a system where private key is not stored anywhere but the same unique private key, assigned to the user by Blockchain, is generated every time with the help of method incorporating biometrics and machine learning. The required data will then be sent to blockchain with the help of IOT system to complete the transaction.

Performance Analysis of Developed Multimodal Biometric Identity Verification System

The bank client identity verification system developed in the course of the IDENT project is presented. The total number of five biometric modalities including: dynamic handwritten signature proofing, voice recognition, face image verification, face contour extraction and hand blood vessels distribution comparison have been developed and studied. The experimental data were acquired employing multiple biometric sensors installed at engineered biometric terminals. The biometric portraits of more than 10 000 bank clients were registered and stored in the database during the presented study and then verified experimentally. Problem- specific survey was done on the basis of questionnaires completed by the subjects in order to assess the look and feel of the developed biometric system as well as to collect opinions concerning its implementation in banking outlets. A discussion concerning the quality of registered data and results achieved in the study is included.

Validating data acquired with experimental multimodal biometric system installed in bank branches

An experimental system was engineered and implemented in 100 copies inside a real banking environment comprising: dynamic handwritten signature verification, face recognition, bank client voice recognition and hand vein distribution verification. The main purpose of the presented research was to analyze questionnaire responses reflecting user opinions on: comfort, ergonomics, intuitiveness and other aspects of the biometric enrollment process. The analytical studies and experimental work conducted in the course of this work will lead towards methodologies and solutions of the multimodal biometric technology, which is planned for further development. Before this stage is achieved a study on the data usefulness acquired from a variety of biometric sensors and from survey questionnaires filled in by banking tellers and clients was done. The decision-related sets were approximated by the Rough Set method offering efficient algorithms and tools for finding hidden patterns in data. Prediction of evaluated biometric data quality, based on enrollment samples and on user subjective opinions was made employing the developed method. After an introduction to the principles of applied biometric identity verification methods, the knowledge modelling approach is presented together with achieved results and conclusions.

Automatic usability and stress analysis in mobile biometrics

This article focuses on the usability evaluation of biometric recognition systems in mobile devices. In particular, a behavioural modality has been used: the dynamic handwritten signature. Testing usability in behavioural modalities involves a big challenge due to the number of degrees of freedom that users have in interacting with sensors, as well as the variety of capture devices to be used. In this context we propose a usability evaluation that allows users to interact freely with the system while minimizing errors at the same time. The participants signed in a smartphone with a stylus through the different phases in the use of a biometric system: training, enrolment and verification. In addition, a profound study on the automation of the evaluation processes has been done, so as to reduce the resources employed. The influence of the users' stress has also been studied, to obtain conclusions on its impact on both the usability systems in scenarios where the user may suffer a certain level of stress, such as in courts, banks or even shopping. In brief, the results shown in this paper prove not only that a dynamic handwritten signature is a trustable solution for a large number of applications in the real world, but also that the evaluation of the usability of biometric systems can be carried out at lower costs and shorter duration.

Score level fusion approach in dynamic signature verification based on hybrid wavelet-Fourier transform

In this work, a dynamic handwritten signature verification system based on hybrid discrete wavelet transform and discrete Fourier transform is presented. Wavelet transform is adopted to analyze the signature information in a multi-resolution representation while retaining its local information by decomposing the signature into different sub-bands. Fourier transform is performed to extract the feature descriptor of the decomposed sub-bands. A dissimilarity score of the extracted features between the test signature and reference data is computed using Euclidean distance and enveloped Euclidean distance. Apart from that, several score level fusion mechanisms have been investigated to combine decisive information to boost up the system performance. The k-nearest neighbor and support vector machine are applied in order to fuse multiple features. The resulting score value is then normalized and compared with a threshold value in order to decide whether a given signature is genuine or forgery. Experiments are conducted on a released version of benchmark SVC2004 database. Two datasets Task 1 and Task 2, which have different types of signature information, are used to evaluate the proposed system, and promising verification results are achieved. Copyright © 2013 John Wiley & Sons, Ltd.

Biometric key generation based on writing force and trajectory

In this paper, key generation algorithm was put forward to safely transform dynamic handwritten signature to biometric key based on F-Tablet, which used Fourier transform to extract feature and multi-state discretization algorithm to generate stable key. The authentication performance and security performance were analyzed through experiment. The key is hard to decrypt and easy to carry, can't be stolen and won't burden users with memory. And the key could be applied in identity authentication, file encryption and digital rights management and so on.