An Approach to Improve Accuracy Rate of On-line Signature Verification Systems of Different Sizes

Abstract

This paper discusses the problem of size variation in on-line signature verification systems. The main idea of the article is to investigate the influence of the size variation in the feature extraction techniques and how this distortion can affect the final classification performance of the systems. In this study a new classification approach was suggested based on Kholmatov and Yanikoglu work in order to measure this performance. Besides that, a feature selection technique was applied in the description of the patterns with the purpose of over come the size variation problem. All the experiments were performed in a database constructed with signatures of three different sizes and skilled forgeries. This kind of study plays an important role in the implementation of systems that uses different signature sources.