Secure surface identification codes

F. Beekhof; S. Voloshynovskiy; O. Koval; R. Villan; T. Pun

doi:10.1117/12.765118

18 March 2008 Secure surface identification codes

F. Beekhof, S. Voloshynovskiy, O. Koval, R. Villan, T. Pun

Proceedings Volume 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X; 68190D (2008) https://doi.org/10.1117/12.765118
Event: Electronic Imaging, 2008, San Jose, California, United States

Abstract

This paper introduces an identification framework for random microstructures of material surfaces. These microstructures represent a kind of unique fingerprints that can be used to track and trace an item as well as for anti-counterfeiting. We first consider the architecture for mobile phone-based item identification and then introduce a practical identification algorithm enabling fast searching in large databases. The proposed algorithm is based on reference list decoding. The link to digital communications and robust perceptual hashing is shown. We consider a practical construction of reference list decoding, which comprizes computational complexity, security, memory storage and performance requirements. The efficiency of the proposed algorithm is demonstrated on experimental data obtained from natural paper surfaces.

Citation Download Citation

F. Beekhof, S. Voloshynovskiy, O. Koval, R. Villan, and T. Pun "Secure surface identification codes", Proc. SPIE 6819, Security, Forensics, Steganography, and Watermarking of Multimedia Contents X, 68190D (18 March 2008); https://doi.org/10.1117/12.765118

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available