Data Glove

A SEMINAR REPORT ON

DYNAMIC SIGNATURE RECOGNITION

SUBMITTED BY

PRIYANKA VERMA (E371)

ASHWINI VICHARE (E372)

UNDER THE GUIDANCE OF

Ms. SEEMA HANCHATE

USHA MITTAL INSTITUTE OF TECHNOLOGY

S. N. D. T. WOMEN’S UNIVERSITY

MUMBAI – 400049

2011 – 2012

Abstract

Handwritten signature is one of the most widely used biometric traits for authentication of person as well as document. Data glove is a new dimension in the field of virtual reality environments, initially designed to satisfy the stringent requirements of modern motion capture and animation professionals. Various sensor technologies are used in the data glove to capture physical data and movement of the hand and fingers such as bending of fingers during the signing process. The data glove technique offers multiple degrees of freedom for each finger and for the hand as well. For electronic information exchange purposes, it is highly desirable to automate the process of accurately identifying genuine and forged signatures. The data glove signature verification technique is tested with large number of authentic and forgery signatures and shows remarkable level of accuracy in finding the similarities between genuine samples as well as the differences between genuine-forgery trials.

Handwritten signature verification is a well-established and potential area of research with numerous applications such as commercial (e.g., Credit card, bank check verification etc.), government (e.g., National ID card, Driver’s license, passport control etc.) and forensic (e.g., corpse identification) application. In this report, we propose a new approach to deal with the problem of handwritten signature verification and forgery detection using data glove.

Introduction

Handwritten signature verification is the process of confirming the identity of a user based on the handwritten signature of the user as a form of behavioral biometrics. Signature verification is one of the most important...