Evaluation of Online Signature Verification Features Ghazaleh Taherzadeh*, Roozbeh Karimi*, Alireza Ghobadi*, Hossein Modaberan Beh** * Faculty of Information Technology Multimedia University, Selangor, Malaysia Gazaleh.taherzadeh07@mmu.edu.my roozbeh.karimi06@mmu.edu.my alireza.ghobadi@mmu.edu.my ** SOHA Sdn. Bhd. Cyberjaya, Selangor, Malaysia modaber@soha.com.my Abstract— in this paper, the methods used by literature to address online signature verification is studied. We propose new set of combination of current features to challenge the online signature verification. At the end, we examine one of the aforementioned methods and show the results. This research explains the classified biometrics elements in two main categories: physical and behavioural. Keywords— Online Signature Verification; Feature Selection; Feature Extraction I. INTRODUCTION In these past few years, due to development and usage of communication and technology in industry, such as banking, verification for evaluating entry application, and password substitutions and etc., there is an increasing need of enhancing level of trust and applying security using biometrics elements which are also known as authentication techniques [1]. Biometrics elements are classified into two main categories: physical and behavioural [2]. Among all these biometrics elements, signature verification is considered as one of the most reliable and effective approaches in security field. Signature verification is categorized into two main types: Static and Dynamic. Static type which is also known as Off- line verification is the process of verifying signature using pen and paper. Dynamic type, which is also known as On-line verification, is the process of verifying signature using digital pen and tablet PC. The main aim of these two methods is to compare the signature in query to the pervious sample of the signer’s signature by computer and special software. Reliable signature verification can be employed in many applications areas such as banking, law enforcement, industry, and security control. Signature verification owns best reliability among others methods, since for stolen signature the user can change or modify his/her signature whereas he/she cannot change the unique characteristics such as face or finger print. On the other hand, online signature verification uses the dynamic information such as speed, and pressure which are achieved by some special instruments during signing process. It also displays better results in contrast with static signature. Numerous methods and algorithms have been proposed to address this problem [3-6]. Many global and local features have been employed in order to evaluate the effectiveness of these methods and algorithms [7-8]. Many Researchers has been achieved to the discriminatory power and high consistency of these features. However, the analysis and measurement of these features individually have not been paid attention adequately. In this paper, the current study on online signature verification methodologies and features was studied and analysed. The experimental work was conducted on analysing and evaluating all the features of online signature verification and combination of its features. According to previously achieved results found in literature, a comparative study was also done on the features and the detail of usage of each feature. The process of our experimental work and signature verification include five steps as follow: 1) Data Acquisition: collect data from existed databases; 2) Pre-processing: contains three stages: i) Normalization, ii) Re-sampling, iii) Smoothing; 3) Feature extraction; 4) Feature matching; 5) Result. II. SIGNATURE VERIFICATION OVERVIEW Signature verification is the process used to recognize an individual's handwritten signature in order to prevent fraud. Signature verification is the task of authenticating a person based on his/her signature. Online (dynamic) signatures are signed on pressure sensitive tablets that capture dynamic properties of a signature in addition to its shape, while offline (static) signatures consist of only the shape information. Dynamic features, such as the coordination and the pen’s pressure at each point along the signature's trajectory, make online signatures more unique and more difficult to forge in comparison with offline signatures. III. SIGNATURE VERIFICATION METHODOLOGY The first off-line and on-line signature verification respectively conducted by Nagel and Rosenfeld and Liu and Herbst [9]. In the following of these studies, varieties of methods and algorithms have been proposed to tackle this problem. Among the proposed methods, several approaches achieved higher prediction accuracy and lower rate of error than the others. Furthermore, much research has followed ISBN 978-89-5519-155-4 772 Feb. 13~16, 2011 ICACT2011