Iris feature based watermarking algorithm for personal identification

Gui Feng; Qiwei Lin

doi:10.1117/12.748180

14 November 2007 Iris feature based watermarking algorithm for personal identification

Gui Feng, Qiwei Lin

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679045 (2007) https://doi.org/10.1117/12.748180
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

Rapidly development of technique causes big problem on the security of digital product. The digital signature technique and watermarking technique are common used solution, but hidden security trouble is still existed. A new biometric watermarking scheme is proposed for property protecting and digital product owner identification. The scheme adopts the iris of digital product holder as watermark, which has the advantage of uniqueness, stability and impossible been counterfeited, so the security level is improved. In this scheme, we utilize person's iris to generate the watermark, and embed this watermark signal into the host image like certification of consumer or other document. While identifying or verifying the owner of the product, we first extract and reconstruct the watermark, then compare the watermark (i.e. the iris image) with the field collected iris image to verify authority. Because there is a direct relationship between the certification holder and the credentials; the reliability is improved greatly.

Citation Download Citation

Gui Feng and Qiwei Lin "Iris feature based watermarking algorithm for personal identification", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679045 (14 November 2007); https://doi.org/10.1117/12.748180

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