Acoustooptic Image Correlators

Eung Gi Paek; Cheol Hoon Park; Fai Mok; Demetri Psaltis

doi:10.1117/12.964260

15 October 1986 Acoustooptic Image Correlators

Eung Gi Paek, Cheol Hoon Park, Fai Mok, Demetri Psaltis

Proceedings Volume 0638, Hybrid Image Processing; (1986) https://doi.org/10.1117/12.964260
Event: 1986 Technical Symposium Southeast, 1986, Orlando, United States

Abstract

Two dimensional correlation for performing image recognition is one of the earliest examples of optical information processing suggested by Vander Lugt and it still remains one of the most promising application areas for this technology. The reasons optical image correlators have not found to this day widespread usage in pattern recognition systems fall into two categories: algorithmic limitations and lack of devices. Correlation-based pattern recognition algorithms have well known limitations such as scale and rotational sensitivity. Over the years algorithms based on optical correlation have been developed, which show promise for overcoming some of the algorithmic limitations, however they have not been put to a real practical test because of the lack of two dimensional spatial light modulators that are necessary for the implementation of the classic Vander Lugt correlator. Specifically, two separate two dimensional SLMs are needed, one for recording the input image and another for the reference.

Citation Download Citation

Eung Gi Paek, Cheol Hoon Park, Fai Mok, and Demetri Psaltis "Acoustooptic Image Correlators", Proc. SPIE 0638, Hybrid Image Processing, (15 October 1986); https://doi.org/10.1117/12.964260

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