Paper
4 September 1998 Infrared-based land mine detection on a vehicle
Chanchal Chatterjee
Author Affiliations +
Abstract
The paper discusses a new method of land-mine detection with a multi-stage algorithm for an infrared (IR) sensor mounted on a vehicle. In recent years, IR-based detection systems have gained increasing interest for the land-mine detection problem. We propose a novel processing technique for the IR sensor. The method consists of five algorithmic stages: (1) pre-processing, (2) preliminary detection, (3) feature extraction, (4) classification, and (5) combination of multiple classifiers. The pre-processing step uses a novel adaptive filtering technique that enhances the mines with respect to the background by an online algorithm. The pre- processed IR image is analyzed by parametric and non- parametric methods of testing differences of means for populations from two distributions. We identify candidate regions of interest at the preliminary detection stage, from which we extract features for classification. We use three different classifiers which are based upon a (1) probabilistic neural network, (2) decision tree, and (3) multi-layer feed- forward neural network. Results from multiple classifiers are combined using a new technique of dynamic classifier selection. We apply the complete algorithm on images acquired by IR cameras mounted on a vehicle, and the preliminary test results are very encouraging.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chanchal Chatterjee "Infrared-based land mine detection on a vehicle", Proc. SPIE 3392, Detection and Remediation Technologies for Mines and Minelike Targets III, (4 September 1998); https://doi.org/10.1117/12.324182
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KEYWORDS
Wavelets

Infrared sensors

Neural networks

Land mines

Image enhancement

Feature extraction

Sensors

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