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Image Processing Methods Applied to Landmine Detection in Ground Penetrating Radar

dc.contributor.advisor Collins, Leslie M
dc.contributor.author Sakaguchi, Rayn Terin Tatsuma
dc.date.accessioned 2013-05-13T15:38:01Z
dc.date.available 2013-05-13T15:38:01Z
dc.date.issued 2013
dc.identifier.uri http://hdl.handle.net/10161/7318
dc.description.abstract <p>Recent advances in statistically based ground penetrating radar (GPR) landmine detection have utilized 2-D slices of data to recognize the hyperbolic shapes caused by a sub-surface landmine. The objective in this research is to identify these shapes using methodology found in the field of image processing. Three different recognition methods were considered; (1) instance matching, which aims to recognize occurrences of a specific object; (2) object detection, which aims to find objects belonging to a class of objects; and (3) category recognition, which aims to categorize entire images based upon the contents of each image. This research consists of the adaptation and evaluation of these methods applied to GPR landmine detection. The results from this work illustrate the additional information that these methods provide to the GPR detection system. In addition, this work shows promise for the application of additional methods from the image processing and computer vision fields.</p>
dc.subject Electrical engineering
dc.title Image Processing Methods Applied to Landmine Detection in Ground Penetrating Radar
dc.type Master's thesis
dc.department Electrical and Computer Engineering


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