Landmine detection using B-spline deformable contours in IR images

Presently, the number of landmines planted around the world totalizes more than 110 million and, far from slowing down, the landmine production planting rate is, at least, one order of magnitude higher than the rate at which they are removed. In this work a technique to detect buried landmines using...

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Autores principales: Gambini, J., Buemi, M.E., Abbatee, H., Castro, E., Berllés, J.J., Santos, J.M., Mejail, M.
Formato: CONF
Materias:
Active contours
B-spline curves
Buried object detection
IR-imagery
Algorithms
Explosives
Infrared imaging
Maximum likelihood
Parameter estimation
B spline curves
IR imagery
Object recognition
Acceso en línea:http://hdl.handle.net/20.500.12110/paper_0277786X_v6553_n_p_Gambini
Aporte de:
Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA) de Universidad de Buenos Aires
id todo:paper_0277786X_v6553_n_p_Gambini
record_format dspace
spelling todo:paper_0277786X_v6553_n_p_Gambini2023-10-03T15:16:36Z Landmine detection using B-spline deformable contours in IR images Gambini, J. Buemi, M.E. Abbatee, H. Castro, E. Berllés, J.J. Santos, J.M. Mejail, M. Active contours B-spline curves Buried object detection IR-imagery Algorithms Explosives Infrared imaging Maximum likelihood Parameter estimation Active contours B spline curves Buried object detection IR imagery Object recognition Presently, the number of landmines planted around the world totalizes more than 110 million and, far from slowing down, the landmine production planting rate is, at least, one order of magnitude higher than the rate at which they are removed. In this work a technique to detect buried landmines using boundary detection in IR images, is presented. The buried objects have different temperature than the surrounding soil. We find the object contours by means of an algorithm of B-Spline deformable curves. Under a statistical model, regions with different temperatures can be characterized by the values of the statistical parameters of these distributions. Therefore, this information can be used to find boundaries among different regions in the image. The B-Spline approach has been widely used in curve representation for boundary detection, shape approximation, object tracking and contour detection. Contours formulated by means of B-Splines allow local control, require few parameters and are intrinsically smooth. The algorithm consists in estimating the parameters along lines strategically disposed on the image. The true boundary is found when the values of these parameters vary abruptly on both sides. A likelihood function is maximized to determine the position of such boundaries. We present the experimental results, which show the behavior of the detection method, according to the buried object depth and the elapsed time from the cooling initial time. The obtained results exhibit that it is possible to recognize the shape of the objects, buried at different depths, with a low computational effort. Fil:Gambini, J. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Buemi, M.E. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Santos, J.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Fil:Mejail, M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. CONF info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_0277786X_v6553_n_p_Gambini
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Active contours
B-spline curves
Buried object detection
IR-imagery
Algorithms
Explosives
Infrared imaging
Maximum likelihood
Parameter estimation
Active contours
B spline curves
Buried object detection
IR imagery
Object recognition
spellingShingle Active contours
B-spline curves
Buried object detection
IR-imagery
Algorithms
Explosives
Infrared imaging
Maximum likelihood
Parameter estimation
Active contours
B spline curves
Buried object detection
IR imagery
Object recognition
Gambini, J.
Buemi, M.E.
Abbatee, H.
Castro, E.
Berllés, J.J.
Santos, J.M.
Mejail, M.
Landmine detection using B-spline deformable contours in IR images
topic_facet Active contours
B-spline curves
Buried object detection
IR-imagery
Algorithms
Explosives
Infrared imaging
Maximum likelihood
Parameter estimation
Active contours
B spline curves
Buried object detection
IR imagery
Object recognition
description Presently, the number of landmines planted around the world totalizes more than 110 million and, far from slowing down, the landmine production planting rate is, at least, one order of magnitude higher than the rate at which they are removed. In this work a technique to detect buried landmines using boundary detection in IR images, is presented. The buried objects have different temperature than the surrounding soil. We find the object contours by means of an algorithm of B-Spline deformable curves. Under a statistical model, regions with different temperatures can be characterized by the values of the statistical parameters of these distributions. Therefore, this information can be used to find boundaries among different regions in the image. The B-Spline approach has been widely used in curve representation for boundary detection, shape approximation, object tracking and contour detection. Contours formulated by means of B-Splines allow local control, require few parameters and are intrinsically smooth. The algorithm consists in estimating the parameters along lines strategically disposed on the image. The true boundary is found when the values of these parameters vary abruptly on both sides. A likelihood function is maximized to determine the position of such boundaries. We present the experimental results, which show the behavior of the detection method, according to the buried object depth and the elapsed time from the cooling initial time. The obtained results exhibit that it is possible to recognize the shape of the objects, buried at different depths, with a low computational effort.
format CONF
author Gambini, J.
Buemi, M.E.
Abbatee, H.
Castro, E.
Berllés, J.J.
Santos, J.M.
Mejail, M.
author_facet Gambini, J.
Buemi, M.E.
Abbatee, H.
Castro, E.
Berllés, J.J.
Santos, J.M.
Mejail, M.
author_sort Gambini, J.
title Landmine detection using B-spline deformable contours in IR images
title_short Landmine detection using B-spline deformable contours in IR images
title_full Landmine detection using B-spline deformable contours in IR images
title_fullStr Landmine detection using B-spline deformable contours in IR images
title_full_unstemmed Landmine detection using B-spline deformable contours in IR images
title_sort landmine detection using b-spline deformable contours in ir images
url http://hdl.handle.net/20.500.12110/paper_0277786X_v6553_n_p_Gambini
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