In recent years, along with the extraordinary diffusion of the Internet and a growing need for personal verification in many daily applications, automatic signature verification is being considered with renewed interest. This paper presents the state of the art in automatic signature verification. It addresses the most valuable results obtained so far and highlights the most profitable directions of research to date. It includes a comprehensive bibliography of more than 300 selected references as an aid for researchers working in the field.

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Automatic Signature Verification: The State of the Art

A review of biometric technology along with trends and prospects

Development of a Sigma-Lognormal representation for on-line signatures

The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. In fact, retrieval of semantically unstructured data entities requires a form of aggregated qualification that selects entities relevant to a query. A popular type of such a mechanism is similarity querying. For a long time, the database-oriented applications of similarity search employed the definition of similarity restricted to metric distances. Due to its topological properties, metric similarity can be effectively used to index a database which can then be queried efficiently by so-called metric access methods. However, together with the increasing complexity of data entities across various domains, in recent years there appeared many similarities that were not metrics—we call them nonmetric similarity functions. In this article we survey domains employing nonmetric functions for effective similarity search, and methods for efficient nonmetric similarity search. First, we show that the ongoing research in many of these domains requires complex representations of data entities. Simultaneously, such complex representations allow us to model also complex and computationally expensive similarity functions (often represented by various matching algorithms). However, the more complex similarity function one develops, the more likely it will be a nonmetric. Second, we review state-of-the-art techniques for efficient (fast) nonmetric similarity search, concerning both exact and approximate search. Finally, we discuss some open problems and possible future research trends.

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On nonmetric similarity search problems in complex domains

Security and protection of personal data are becoming more and more important. At the same time, we see a steady rise of very powerful mobile devices like smartphones and tablets. These devices offer most capabilities of desktop computers. Even today, they are often used for storing or accessing individual data. In the near future, it is obviously desirable to use their Internet capability to access private data or even business intra-nets from everywhere. Therefore, new security mechanisms must be designed. In this paper, we only focus on the authentication part (and ignore OS and network issues). Traditional methods for authentication (like smartcards or face recognition) may not be used in every context because of hardware and environment limitations (dark environments or camera restrictions in business). Therefore, we suggest to develop a mixture of a keystroke-based and a handwriting-based authentication method using capacitive displays. In this paper, we will briefly discuss limitations of existing approaches and why we believe that keystroke and handwriting authentication is a possible way for improving the security on mobile devices. First experiments will demonstrate the effectivity of this new approach with error rates under 2%.

Toward Mobile Authentication with Keystroke Dynamics on Mobile Phones and Tablets

Authentication based on handwritten signature is the most accepted authentication system based on biometry because it is easy to use and because the use of signature is part of our habits. In the field of authentication by on-line signature, we present a method to reduce the amount of data to be stored for pattern comparison and that needs few processing. Many systems described in literature keep the whole signature's points even if it is not recommended, even advised against it, in order to avoid forgers to obtain a signature's pattern. The proposed method for data reduction was evaluated with respect to a method of curve comparison very often used for authentication by on-line handwritten signature: dynamic time warping (DTW). After we have presented several reduction methods of signature data, we show the results obtained with each one. In order to evaluate their efficiency, the results were compared to those obtained with the whole coarse data points of the signature.

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Selection of points for on-line signature comparison

Authentication by handwritten on-line signature is one of the most accepted authentication system In a way, it is based on biometrics It is embedded in our cultural habits and easy to use The aim of this paper is to study two possible improvements in Dynamic Time Warping: matching process and distance computation After applying a polygonal approximation on the signatures, we test different approaches on the authentication problem Usually, the information used to match the on-line signatures are the coordinates or the speed at the input data points First, as far as the matching is concerned, we investigate other possibilities relying on the local information at each point Next, we also test several methods to take into account local information to compute the distance To limit genuine signature rejections, we use the result of the matching as a way to detect forgery and we also modify the computation of the distance Finally, we evaluate the different approaches on a base of 800 signatures The results obtained show an amelioration of the classical use of DTW

Improving DTW for Online Handwritten Signature Verification

Authentication by on-line handwritten signature is one of the most accepted authentication way, this is due to its easy use and to our cultural habits. In order to improve performances of the authentication process, we propose to take into account, on one part, the global temporal aspect and the efficiency of the writing of the signature and, on the other part, the signature variability of a person by using the only available information, the training signatures. To improve the robustness of the process we propose a method which consists of selecting the representative points in the signature. Curves comparison is based on dynamic time warping (DTW) in an original way. The different methods elaborated are tested on two databases of signatures and compared with the standard use of DTW. It shows the relevance of the improvements. All the modifications that we have presented will allow to obtain an improvement of more than 15%.

Distance and matching for authentication by on-line signature

Authentication by handwritten signature is the most accepted authentication system based on biometrics partly due to the fact that it is easy to be used and part of our cultural habits. We present some improvement for one of the most important problems in such systems: features construction and selection. Concerning the study of the signature’s shape, we discuss the impact of the selected features on the global system architecture. We propose to extract information linked to the writer by computing new features based on fractal dimension of the on-line signature. In order to prove the interest of these features, several performance evaluation methods are presented. Finally, the results of tests using the combination of new features with classical ones, and a method of features selection using Genetic Algorithm are discussed.

M. Wirotius

Papers

Selection of points for on-line signature comparison

Improving DTW for Online Handwritten Signature Verification

Distance and matching for authentication by on-line signature

New Features for Authentication by On-Line Handwritten Signatures