Cellular automata enabling novel fast shape recognition for muon tomography

Jaenisch, Holger M., Handley, James W., Jaenischa, Kristina L., and Albrittone, Nathaniel G. (2009) Cellular automata enabling novel fast shape recognition for muon tomography. In: Proceedings of SPIE - The International Society for Optical Engineering (7335). From: SPIE 2009 - The International Society for Optical Engineering, 13 -14 April 2009, Orlando, Florida, USA.

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Abstract

We present a simple and efficient muon tomography simulation based on Data Modeling and a fast method for real-time threat target identification in obscured environments. Our approach introduces a fast form of statistical characterization in conjunction with equation based Data Models that makes the use of median calculation and Point of Closest Approach (POCA) reconstruction unnecessary. Our method enables accurate medium to high Z multi-target identification without background subtraction and in less than 10 seconds total processing time. Our method is general and applies to other volumetric/voxel processing as well. © 2009 SPIE.

Item ID: 11540
Item Type: Conference Item (Refereed Research Paper - E1)
Keywords: data modeling; muon imaging; tomography; change detection; shape recognition; cellular automata; bi-spectrum; tri-spectrum; Game of Life
ISBN: 978-0-8194-7601-2
ISSN: 0277-786X
Date Deposited: 15 Jun 2010 22:51
FoR Codes: 02 PHYSICAL SCIENCES > 0201 Astronomical and Space Sciences > 020108 Planetary Science (excl Extraterrestrial Geology) @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970102 Expanding Knowledge in the Physical Sciences @ 100%
Citation Count from Scopus Scopus 2
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