Abstract
A large number of parameters affect the fundamental performance of automatic target recognition (ATR) systems including sensor, geometry, and scene parameters. Clutter complexity refers to the scene parameter that measures the extent that the objects in the background of the scene are target-like. This paper describes our initial work to understand how to measure clutter complexity and bound ATR performance as a function of this complexity, given that the other parameters are held constant. For this study, we use an unrealistically omnipotent ATR to approximate performance bounds and characterize the clutter complexity for each scene in the COMANCHE FLIR database. Using this characterization, we generate a clutter complexity metric from a number of image processing features and compare the new metric against the performance of an actual ATR.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.