Image characterization for automatic target recognition algorithm evaluations

Lloyd G. Clark; Vincent J. Velten

doi:10.1117/12.55784

1 February 1991 Image characterization for automatic target recognition algorithm evaluations

Lloyd G. Clark, Vincent J. Velten

Author Affiliations +

Optical Engineering, Vol. 30, Issue 2, (February 1991). https://doi.org/10.1117/12.55784

Abstract

Automatic object recognizer algorithms designed to work with imaging sensor inputs require extensive testing before they should be considered robust enough for challenging applications such as military targeting. Testing automatic target recognition (ATR) algorithms in most cases has been limited to a handful of the scenario conditions of interest as represented by imagery collected with a desired imaging sensor. The question naturally arises as to how robust the performance of the ATR is for all scenario conditions of interest, not just for a small set of collected imagery. A way of addressing algorithm robustness is to characterize the input imagery in terms of some common information content or quality measures that can be correlated with ATR performance. This paper addresses the utility of image characterization measures in terms of estimating ATR detection performance by correlation analyses between nine different image measures and the detection responses of two ATR algorithms. Results show that an image measure called target-to-background entropy difference is the best single measure for estimating ATR detection performance, with correlation coefficients as large as 0.60.

Citation Download Citation

Lloyd G. Clark and Vincent J. Velten "Image characterization for automatic target recognition algorithm evaluations," Optical Engineering 30(2), (1 February 1991). https://doi.org/10.1117/12.55784

Published: 1 February 1991

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