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Detection of buried objects in FLIR imaging using mathematical morphology and SVM

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4 Author(s)
Mihail Popescu ; Electrical and Computer Engineering Dept., University of Missouri Columbia, Missouri, USA ; Alex Paino ; Kevin Stone ; James M. Keller

In this paper we describe a method for detecting buried objects of interest using a forward looking infrared camera (FLIR) installed on a moving vehicle. Infrared (IR) detection of buried targets is based on the thermal gradient between the object and the surrounding soil. The processing of FILR images consists in a spot-finding procedure that includes edge detection, opening and closing. Each spot is then described using texture features such as histogram of gradients (HOG) and local binary patterns (LBP) and assigned a target confidence using a support vector machine (SVM) classifier. Next, each spot together with its confidence is projected and summed in the UTM space. To validate our approach, we present results obtained on 6 one mile long runs recorded with a long wave IR (LWIR) camera installed on a moving vehicle.

Published in:

2012 IEEE Symposium on Computational Intelligence for Security and Defence Applications

Date of Conference:

11-13 July 2012