Monday, 30 May 2011

Wseas Transactions

New Subscription to Wseas Transactions

The following information was submitted:

Transactions: WSEAS TRANSACTIONS ON SIGNAL PROCESSING
Transactions ID Number: 53-595
Full Name: Tomislav Fotak
Position: Ph.D. Candidate
Age: ON
Sex: Male
Address: 31221 Josipovac, Ulica Marka Marulića 1
Country: CROATIA (HRVATSKA)
Tel: +385981952200
Tel prefix:
Fax:
E-mail address: tomislav.fotak@foi.hr
Other E-mails: tomislav.fotak@gmail.com
Title of the Paper: Handwritten signature identification using basic concepts of graph theory
Authors as they appear in the Paper: Tomislav Fotak, Miroslav Bača, Petra Koruga
Email addresses of all the authors: tomislav.fotak@foi.hr, miroslav.baca@foi.hr, petra.koruga@foi.hr
Number of paper pages: 11
Abstract: Handwritten signature is being used in various applications on daily basis. The problem arises when someone decides to imitate our signature and steal our identity. Therefore, there is a need for adequate protection of signatures and a need for a systems that can, with a great degree of certainty, identify who is the signatory. This paper presents previous work in the field of signature and writer identification to see the historical development of the idea and defines a new promising approach in handwritten signature identification based on some basic concepts of graph theory. This principle can be implemented on both on-line handwritten signature recognition systems and off-line handwritten signature recognition systems. Using graph norm for fast classification (filtration of potential users), followed by comparison of each signature graph concepts value against values stored in database, the system reports 94.25% identification accuracy.
Keywords: Handwritten signature, Signature recognition, Identification, Graph theory, Biometrics, Behavioral characteristics
EXTENSION of the file: .pdf
Special (Invited) Session: Image Processing and 2-D / 3-D Systems
Organizer of the Session:
How Did you learn about congress: Multidimensional systems, Image analysis and segmentation, Classification, Security. Publicity. Privacy. Reputation, Other
IP ADDRESS: 89.201.249.250