Robust entropy-guided image segmentation for ground detection in GPR

J. Roberts; Y. Shkolnikov; J. Varsanik; T. Chevalier

doi:10.1117/12.2016615

7 June 2013 Robust entropy-guided image segmentation for ground detection in GPR

J. Roberts, Y. Shkolnikov, J. Varsanik, T. Chevalier

Proceedings Volume 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII; 87091N (2013) https://doi.org/10.1117/12.2016615
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Identifying the ground within a ground penetrating radar (GPR) image is a critical component of automatic and assisted target detection systems. As these systems are deployed to more challenging environments they encounter rougher terrain and less-ideal data, both of which can cause standard ground detection methods to fail. This paper presents a means of improving the robustness of ground detection by adapting a technique from image processing in which images are segmented by local entropy. This segmentation provides the rough location of the air-ground interface, which can then act as a “guide” for more precise but fragile techniques. The effectiveness of this two-step “coarse/fine” entropyguided detection strategy is demonstrated on GPR data from very rough terrain, and its application beyond the realm of GPR data processing is discussed.

Citation Download Citation

J. Roberts, Y. Shkolnikov, J. Varsanik, and T. Chevalier "Robust entropy-guided image segmentation for ground detection in GPR", Proc. SPIE 8709, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XVIII, 87091N (7 June 2013); https://doi.org/10.1117/12.2016615

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