Experiments of thermographic landmine detection with reduced size and compressed time

Muscio, Alberto; Corticelli, Mauro Alessandro

doi:10.1016/j.infrared.2004.03.014

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…object's depth, shape, and its thermal diffusivity with their two-step method. Muscio et al [34] proposed a method that enables reproduction of thermal properties of outdoor conditions with reduced size of data and compressed time. They generated a generalized formula for this purpose.…”

Section: Thermal Infrared In Landmine Detectionmentioning

confidence: 99%

“…In order to represent frequently encountered landmines, M15 antitank, M16, M2, and M48 metal, DM11, and M14 plastic PLs were used in our study. M15 and plastic mines were filled with wax that represents explosives' thermal characters [34]. Images from the procedure of filling M15 PL, M14, and DM11 with wax can be seen in…”

Section: Preparation Of Practice Landminesmentioning

confidence: 99%

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Buried and Surface Mine Detection From Thermal Image Time Series

Kaya

Leloglu

2017

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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, 117 pages Since many countries suffer from existence of landmines in their territory, there is a growing demand for reliable landmine detection systems. Most of these systems require an operator to enter into the minefield. However, infrared sensor methods can be used remotely; hence, they do not put lives at risk during the search operation. In this thesis, a new approach to the infrared sensor method, which gives promising results, is presented. Buried landmines generate specific spatiotemporal thermal image patterns on the surface. Noise-reduced thermal image time series were used after preprocessing with a circularly symmetric filter different from other studies. Supervised classification methods (Support Vector Machine, Mahalanobis Discriminant Analysis, Quadratic Discriminant Analysis, and K-Nearest Neighbor) are applied on the filtered image series. Proposed method gives promising solutions that were verified with enlarged data sets. Different parameters (humidity, burial depths, training sample sizes, time intervals, seasons, spatial filter's sizes etc.) influences on the solutions were examined. To find the vi most useful time intervals, a 2-D heat transfer simulation was performed. Particularly using image series within nighttime, sunrise, and sunset times allow finding fourcentimeter deep plastic and 6.8-centimeter deep metal practice landmines with the proposed method. The best solutions were got with the 50-pixel outer diameter spatial filter and the 24-sample on this diameter. Detection rates were calculated higher in quasi-humid soil than dry soil.

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Section: Thermal Infrared In Landmine Detectionmentioning

confidence: 99%

Section: Preparation Of Practice Landminesmentioning

confidence: 99%