Automated target recognition technique for image segmentation and scene analysis

Chris W. Baumgart; Christopher A. Ciarcia

doi:10.1117/12.169966

2 March 1994 Automated target recognition technique for image segmentation and scene analysis

Chris W. Baumgart, Christopher A. Ciarcia

Proceedings Volume 2243, Applications of Artificial Neural Networks V; (1994) https://doi.org/10.1117/12.169966
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

Automated target recognition (ATR) software has been designed to perform image segmentation and scene analysis. Specifically, this software was developed as a package for the Army's Minefield and Reconnaissance and Detector (MIRADOR) program. MIRADOR is an on/off road, remote control, multisensor system designed to detect buried and surface- emplaced metallic and nonmetallic antitank mines. The basic requirements for this ATR software were the following: (1) an ability to separate target objects from the background in low signal-noise conditions; (2) an ability to handle a relatively high dynamic range in imaging light levels; (3) the ability to compensate for or remove light source effects such as shadows; and (4) the ability to identify target objects as mines. The image segmentation and target evaluation was performed using an integrated and parallel processing approach. Three basic techniques (texture analysis, edge enhancement, and contrast enhancement) were used collectively to extract all potential mine target shapes from the basic image. Target evaluation was then performed using a combination of size, geometrical, and fractal characteristics, which resulted in a calculated probability for each target shape. Overall results with this algorithm were quite good, though there is a tradeoff between detection confidence and the number of false alarms. This technology also has applications in the areas of hazardous waste site remediation, archaeology, and law enforcement.

Citation Download Citation

Chris W. Baumgart and Christopher A. Ciarcia "Automated target recognition technique for image segmentation and scene analysis", Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); https://doi.org/10.1117/12.169966

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

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
6 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Mining

Image segmentation

Image processing

Land mines

Software development

Automatic target recognition

Image enhancement

Show All Keywords

Keywords/Phrases

Search In:

Publication Years