Detecting explosive hazards in 3D radar imaging through clustering and sequential learning

Q. LaRoe; M. Popescu; J. M. Keller

doi:10.1117/12.2304552

30 April 2018 Detecting explosive hazards in 3D radar imaging through clustering and sequential learning

Q. LaRoe, M. Popescu, J. M. Keller

Proceedings Volume 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII; 1062817 (2018) https://doi.org/10.1117/12.2304552
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

Abstract

In this paper, we present a methodology for detecting side-attack explosive hazards using three-dimensional radar imaging. Our methodology is based on clustering intensities of voxel cubes extracted around points of interest generated from prescreener filters. To make our computations easier, and results visually comprehensible, we break our voxel cubes into slices within the x-, y-, and z-directions of equal dimensions. With these slices, we explore various feature extraction algorithms: K-Means, Fuzzy C-Means (FCM), and statistical moments on the radar intensity slices to create feature vectors based on a set number of cluster centers and number of slices within the extracted cubes. We evaluate the performance of the features produced using Hidden Markov Model (HMM) classifiers on a set of lane data supplied by the US Army.

Citation Download Citation

Q. LaRoe, M. Popescu, and J. M. Keller "Detecting explosive hazards in 3D radar imaging through clustering and sequential learning", Proc. SPIE 10628, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XXIII, 1062817 (30 April 2018); https://doi.org/10.1117/12.2304552

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