Cellular automata enabling novel fast shape recognition for muon tomography

Holger M. Jaenisch; James W. Handley; Kristina L. Jaenisch; Nathaniel G. Albritton

doi:10.1117/12.817833

4 May 2009 Cellular automata enabling novel fast shape recognition for muon tomography

Holger M. Jaenisch, James W. Handley, Kristina L. Jaenisch, Nathaniel G. Albritton

Author Affiliations +

Proceedings Volume 7335, Automatic Target Recognition XIX; 733504 (2009) https://doi.org/10.1117/12.817833
Event: SPIE Defense, Security, and Sensing, 2009, Orlando, Florida, United States

Abstract

We present a novel and detailed algorithm for enabling passive muon tomography systems to be used for 3-D threat object recognition in real-time. Our method makes use of characteristic changes of the Hamming distance curve derived from Cellular Automata rules converted into a novel Data Model form. We show that fragmented and noisy shape images can be adequately processed and recognized without resorting to morphological or traditional template matching approaches. The approach is general and has utility in other target/shape recognition and imaging applications.

Citation Download Citation

Holger M. Jaenisch, James W. Handley, Kristina L. Jaenisch, and Nathaniel G. Albritton "Cellular automata enabling novel fast shape recognition for muon tomography", Proc. SPIE 7335, Automatic Target Recognition XIX, 733504 (4 May 2009); https://doi.org/10.1117/12.817833

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