Paper
18 October 2001 GUI for automated detection of surface mines using iterated hybrid morphological filters
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Abstract
An unsupervised algorithm is proposed for land mine detection in heavily cluttered multispectral images, based on iterating hybrid multi-spectral morphological filters. The hybrid filter used in each iteration consists of a decorrelating linear transform coupled with a nonlinear morphological detection component. Targets, extracted from the first pass, are used to improve detection results of the subsequent iteration, by helping to update covariance estimates of relevant filter variables. The procedure is stopped after a predetermined number of iterations is reached. Current implementation addresses several weaknesses associated with previous versions of the hybrid morphological approach to land mine detection. Improvement in detection accuracy and speed, robustness with respect to clutter inhomogeneity, and a completely unsupervised operation are the main highlights of the proposed approach. Our experimental investigation reveals substantially superior detection performance and lower false alarm rates over previous schemes. Properties of a graphical user interface (GUI), based on the proposed iterative morphological detection scheme, are also discussed.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Sinan Batman, John Ioannis Goutsias, and Manoj B. Palki "GUI for automated detection of surface mines using iterated hybrid morphological filters", Proc. SPIE 4394, Detection and Remediation Technologies for Mines and Minelike Targets VI, (18 October 2001); https://doi.org/10.1117/12.445484
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Image filtering

Signal to noise ratio

Land mines

Mining

Binary data

Target detection

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