Some issues with ATRs based on template matching

John M. Irvine

doi:10.1117/12.339818

29 January 1999 Some issues with ATRs based on template matching

John M. Irvine

Proceedings Volume 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition; (1999) https://doi.org/10.1117/12.339818
Event: The 27th AIPR Workshop: Advances in Computer-Assisted Recognition, 1998, Washington, DC, United States

Abstract

Most Automatic Target Recognition algorithms consist of multiple processing stages, starting with a `detector' to locate objects of potential interest within an image. Then a target `classifier' identifies these objects by assigning them to specific target classes. The classifier uses the localized information in the image to assign each object to one of a number of categories, called targets, or if the object is not classifiable, it might be rejected as not being a target. This paper focuses on the properties associated with certain types of classifiers when applied to synthetic aperture radar (SAR) imagery. A common approach to classification is to construct some type of library of known templates for the targets of interest. The objects flagged by the detector are compared to each template and, based on some figure of merit, the object is classified. A popular classification rule is to calculate the mean squared error (MSE) between the detected object and each template, and assign the object to the target type that minimizes the observed MSE. Although minimization of MSE has some intuitive appeal and is fairly easy to implement, it has undesirable properties when applied to SAR data. In this paper, we investigate the statistical properties associated with MSE classification when the underlying pixel values are drawn from a long-tailed, asymmetric distribution, as is typical for SAR data. More important, however, are the within class sources of variance that arise in realistic scenarios. These sources of variance tend to inflate the MSE, even when the candidate object is compared to the correct template. This paper explores the statistical nature of this problem and illustrates it with a series of example images.

Citation Download Citation

John M. Irvine "Some issues with ATRs based on template matching", Proc. SPIE 3584, 27th AIPR Workshop: Advances in Computer-Assisted Recognition, (29 January 1999); https://doi.org/10.1117/12.339818

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