Data glove is a new dimension in the field of virtual reality environments, initially designed to satisfy the stringent requirements of modern motion capture and animation professionals. In this study we try to shift the implementation of data glove from motion animation towards signature verification problem, making use of the offered multiple degrees of freedom for each finger and for the hand as well. We used an SVD-based technique to extract the feature values of different sensors' locating on corresponding fingers in the signing process and evaluated the results for writer authentication. The technique is tested with large number of authentic and forgery signatures using data gloves with 14, 5 and 4 sensor and shows a significant level of accuracy with 2.46~5.0% of EER.

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A Novel Approach to Dynamic Signature Verification Using Sensor-Based Data glove

A new online signature-verification method using temporal shift estimation is presented. Local temporal shifts existing in signatures are estimated by the differences of the phase outputs of Gabor filter applied to signature signals. In the proposed signature-verification algorithm, an input signature signal undergoes preprocessing procedures including smoothing, size normalization and skew correction, and then its feature profile is extracted from the signature signal. A Gabor filter with the predetermined center frequency /spl omega/ is applied on a feature profile, and a phase profile is computed from the phase output. The feature profile and the phase profile are length normalized and quantized so that a signature code of fixed size is generated. The temporal shifts existing between two signatures are computed by using the differences between the phase profiles. The information about the temporal shifts is used as offsets for comparing the two feature profiles. Therefore, two kinds of dissimilarities are proposed. Temporal dissimilarity is a measure reflecting the amount of total temporal disturbance between the two signatures. The difference between the two signature profiles is computed at each corresponding point pair and is accumulated into temporally arranged feature profile dissimilarity. The decision boundary is represented as a straight line in the dissimilarity space whose two axes are the two dissimilarity measures. The slope and the position of the decision boundary are computed using the distribution of the dissimilarities among the sample signatures involved in the enrollment procedure. The experimental results show that through the compact and fixed size of signature data representation and relatively simple comparison methods, the proposed method can compare signatures 400 times faster than the conventional DP matching based signature-verification method.

Online signature verification using temporal shift estimated by the phase of Gabor filter

Handwritten signature verification is a well-established and potential area of research with numerous applications such as commercial (e.g., credit card, bank check verification etc.), government (e.g., National ID card, Driver's license, passport control etc.) and forensic (e.g., corpse identification) application. In this paper, we propose a new approach to deal with the problem of handwritten signature verification and forgery detection using data glove. The technique is based on linearly projecting the glove signature into a low-dimensional space, through the singular value decomposition (SVD). The Euclidean distance between the different groups of singular values is used to measure the authenticity of the tried signatures. The reliability and efficiency of the proposed system against forgeries are tested and reported. A comparative analysis has also been shown for data gloves with 14, 5, and 4 sensors respectively

Dynamic Signature Verification Using Sensor Based Data Glove

Signatures continue to be an important biometric because they remain widely used as a means of personal verification and therefore an automatic verification system is needed. Manual signature-based authentication of a large number of documents is a difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable unique physical characteristics (e.g. hand geometry, iris scan, finger prints or DNA) or behavioural features. Substantial research has been undertaken in the field of signature verification involving English signatures, but to the best of our knowledge, very few works have considered non-English signatures such as Chinese, Japanese, Arabic etc. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of non-English and non-Latin signature verification systems.

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Non-English and Non-Latin Signature Verification Systems: A Survey

This paper accounts the testing protocols used at the author's university. It examines the experiences of one particular study in dynamic signature verification. The paper also outlines some additions to the current testing methodologies.

Development of a biometric testing protocol for dynamic signature verification

Signature verification is a natural and friendly approach in biometrics-based verification. As we know, the system can achieve a better performance if more training samples are collected. However, routinely signing the patterns is a boring and inconvenient process to obtain enough training samples at the initial enrolment. In this paper, we have proposed a multi-template matching approach to identify the individual via few training samples. Some experimental results were conducted to show the effectiveness of our proposed methods.

An on-line signature verification system using multi-template matching approaches

On-line signature verification is a technique to verify the digital on-line signature signal with the signature template of a specified person for personal identification. In this paper, an on-line handwriting Chinese signature verification system based on weighted-multiexpert strategy is proposed. First, the present researches of signature verification and the structure of our proposed system are described. Then, the feature extraction, genuine model, imitative model and multi-expert decision method are described. Finally, the practical experimental results and conclusions are discussed.

Pao-Chung Chang

Papers

An on-line signature verification system using multi-template matching approaches

On-line Chinese signature verification based on multi-expert strategy