An approach for signature recognition using contours based technique
C. V. Aravinda, Lin Meng, Uday Kumar Reddy K. R. · 2019
This research work addresses the problem of signature verification and recognition using contours based features and ANN classifier. In this work new features are proposed for signature verification and recognition. As extensive research works has been carried out in the area of HSVR signature verification and recognition by several researchers over the past two decades, many methodologies found in the literature survey. Signature plays a vital role in many fields, generally it is used for personal authentication or gaining control over a system or computing facility, physical entry to protected areas. The signature biometric problem has 2 different perspectives based on PR. 1) Verification and 2) Recognition. In verification, features of a test signature are contrasted with features of a limited set signatures, where the class identity is claimed, whereas, in recognition, the presence of an identity test signature in the database is ascertained. There are two types of variations in signature samples Intraclass variations Interclass variations Intraclass variations are intricate variations of a person's signature, and interclass variations are refer to variations of different person's signature. In this exploration work, problem of effective HSVR is addressed. We propose effective feature extraction and combination of features for verification and recognition of signatures. Recognition involves FM-stage that extends to entire database.