A New Signature Similarity Measure Based on Windows Allocation Technique

Abstract

The paper presents a new signature similarity measure and new efficient method of recognizing handwritten signatures. Each signature is represented as a set of features such as coordinates of signature points, pen pressure, and speed of writing. Proposed approach consists in dividing signature into windows and calculating similarity values between individual windows. The influence of the size of windows and their location in a signature has been analysed. Additionally, the influence of individual features on the signature similarity value has been examined. Proposed in this paper similarity coefficient has been compared to other similarity measures. Effectiveness of the presented method has been also presented and compared with other approaches.