원문정보
초록
영어
A digital signature is a mathematical structure for indicating the validity of digital information or any document. A message is created by a known sender whose digital signature provides a recipient reason, such that the sender cannot reject having sent the message confirmation and that the message was not changed in transportation integrity. The Signature recognition and verification are a behavioral biometric. It can be operated in two various types: one is the Off-Line or Static Signature Verification Technique and another is the On-line or Dynamic Signature Verification Technique. In this paper, we are studying about Off-Line or Static Signature Verification Technique. In this method, users write their own signature on the blank paper and then digitize it with an optical scanner or a camera, and then the biometric system identifies the signature by analyzing its shape and this collection is also called as “off-line” Signature verification. Signature authentication can be divided into three main classes. These classes are based on how alike a forgery is in relation to signature and are identified as random, simple and skilled. In the random forgery the forger does not know about the signer’s shape or signature name. In the simple forgery or unskillful forgery, the forger knows the name of the actual signer but don’t know how his signature looks like. And in the skilled forgery, the forger knows both the information of the signer.
목차
1. Introduction
2. Type of Signature Verification
2.1. Off-line or Static Signature Verification Method:
2.2. On-line or Dynamic Signature Verification Method:
3. Feature Extraction
3.1. Invariant Central Moment :
3.2. Zernike Moments :
4. Literature View
5. Methodology
5.1 Hidden Markov Models Approach
5.2 Neural Networks Approach
5.3 Template Matching Approach
5.4 Statistical Approaches
5.5 Support Vector Machine
6. Conclusion
References