Error reduction in reconstruction of kinoform CGH patterns for a hologram ID tag system

Hye-Rim Kim; Ki-Mun Pak; Ji-Song Lim; Yong-Hyub Won

doi:10.1117/12.858951

7 June 2010 Error reduction in reconstruction of kinoform CGH patterns for a hologram ID tag system

Hye-Rim Kim, Ki-Mun Pak, Ji-Song Lim, Yong-Hyub Won

Proceedings Volume 7730, Optical Data Storage 2010; 77301O (2010) https://doi.org/10.1117/12.858951
Event: Optical Data Storage 2010, 2010, Boulder, Colorado, United States

Abstract

In this paper, we propose a hologram reconstruction algorithm with techniques which can effectively reduce reconstruction errors caused from reconstruction process and external damages of the kinoform CGH ID tag. The 11- level kinoform computer generated hologram (CGH) patterns which are generated by modified simulated annealing are recorded on a texture paper by a photo printer, and retrieved by a digital camera. Through suitable reconstruction program and image processing in computer, the captured hologram patterns on the ID tag are reconstructed with a low error rate of about 4%, compared to the original data prior to the kinoform CGH pattern. It is also shown that our robust reconstruction algorithm can considerably reduce reconstruction errors for damaged tags. The original image has been actually reconstructed at a low error rate of about 8% and 12% from a 25% and 50% damaged tag, respectively.

Citation Download Citation

Hye-Rim Kim, Ki-Mun Pak, Ji-Song Lim, and Yong-Hyub Won "Error reduction in reconstruction of kinoform CGH patterns for a hologram ID tag system", Proc. SPIE 7730, Optical Data Storage 2010, 77301O (7 June 2010); https://doi.org/10.1117/12.858951

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