A morphological approach to automatic mine detection problems

Author

Banerji, Ashish ; Goutsias, John

Author_Institution

Dept. of Electr. & Comput. Eng., Johns Hopkins Univ., Baltimore, MD, USA

Volume

34

Issue

4

fYear

1998

fDate

10/1/1998 12:00:00 AM

Firstpage

1085

Lastpage

1096

Abstract

We consider the problem of detecting mines and minelike targets imaged by multispectral sensors. We propose an algorithm, based on mathematical morphology (MM), that yields accurate detection results in moderately cluttered environments. For targets in heavily cluttered environments, a preprocessing step is employed, based on the maximum noise fraction (MNF) transform, in order to reduce the effect of clutter and enhance the presence of targets. The algorithm is simple, performs well, and requires only approximate knowledge of target size

Keywords

clutter; covariance matrices; image reconstruction; image registration; image sequences; mathematical morphology; object detection; sensor fusion; accurate detection results; automatic mine detection problems; covariance matrices; data fusion; heavily cluttered environments; mathematical morphology; maximum noise fraction transform; minelike targets; moderately cluttered environments; morphological approach; morphological image reconstruction; multispectral optical sensors; preprocessing step; Image sensors; Landmine detection; Layout; Marine technology; Military computing; Object detection; Optical filters; Optical imaging; Optical sensors; Sea measurements;

fLanguage

English

Journal_Title

Aerospace and Electronic Systems, IEEE Transactions on

Publisher

ieee

ISSN

0018-9251

Type

jour

DOI

10.1109/7.722683

Filename

722683