Paper Info
Title
Detecting and locating landmine fields from vehicle- and air-borne measured IR Images
Abstract
Air- and vehicle-borne sensor-based technique is a potentially attractive approach for fast detecting landmines and locating landmine fields towards humanitarian demining. For images measured from airborne and vehicle-borne cameras, landmines may be indicated by direct or indirect signs, e.g., spatial difference from their surroundings due to digging or, due to thermal and material signatures. The background in images usually consists of various types of noise and clutter, e.g., thermal noise, sand, gravel road and vegetation, thus making the detection even more difficult. This paper is focused on the following aspects: (1) Finding a robust detector that is suitable for detecting/locating landmine candidates and man-made landmarks by using infrared images measured from vehicle- or air-borne sensors; (2) Interpreting the detector using the 2D isotropic bandpass filter, matched filter, detection theory and thermodynamic-based landmine models; (3) Extending the detector to a multiscale version where landmine detectability is enhanced by automatically selecting a proper scale and localization is improved by inter-scale position tracing. We propose a special type of isotropic feature detector that exploits the characteristic difference between landmines and their surroundings in the spatial-frequency domain under the multiscale framework. Experiments were performed on several infrared images measured from vehicle-borne sensors as well as airborne sensors on a helicopter over the test bed scenarios. The performance of the detector was also evaluated in terms of detectability, localization, and automatic scale selection of the detector. These results and evaluations have shown the effectiveness of the method and its potential in landmine field detection.
Year
DOI
Venue
2002
10.1016/S0031-3203(02)00020-1
Pattern Recognition
Keywords
Field
DocType
Landmine detection,Locating landmine fields,Airborne imaging,Vehicle-borne imaging,Infrared (IR) images,Feature detection,Matched filter,Isotropic filter,Multiresolution analysis,Target enhancement
Computer vision,Band-pass filter,Detection theory,Clutter,Noise (electronics),Multiresolution analysis,Artificial intelligence,Matched filter,Detector,Tracing,Mathematics
Journal
Volume
Issue
ISSN
35
12
0031-3203
Citations 
PageRank 
References 
5
0.89
12
Authors
2
Name
Order
Citations
PageRank
Irene Yu-Hua Gu161335.06
Tardi Tjahjadi240627.85