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Proceedings Paper

Detection of minelike targets using grayscale morphological image reconstruction
Author(s): Ashish Banerji; John Ioannis Goutsias
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Paper Abstract

Automatic target detection is the primary goal of many imaging systems both in defense and manufacturing industries. Advances in methods and equipment for image acquisition, processing, and analysis are required to effectively deal with this problem. Towards this goal, we discuss here a target detection algorithm based on mathematical morphology. Mathematical morphology is an image processing tool that is used for designing nonlinear operators for image representation, processing, and analysis. In particular, the proposed approach is based on a morphological reconstruction algorithm for detecting targets of interest appearing on a scene. We apply this algorithm to the problem of detecting minelike targets in multispectral images, provided to us by the Coastal Systems Station, Naval Surface Warfare Center, Panama City, Florida. The proposed technique is relatively simple and only requires approximate knowledge of target size. The algorithm also effectively incorporates fusion of data from different bands. The implementation has been done in the KHOROS signal and image processing environment with encouraging results.

Paper Details

Date Published: 20 June 1995
PDF: 14 pages
Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); doi: 10.1117/12.211377
Show Author Affiliations
Ashish Banerji, Johns Hopkins Univ. (United States)
John Ioannis Goutsias, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 2496:
Detection Technologies for Mines and Minelike Targets
Abinash C. Dubey; Ivan Cindrich; James M. Ralston; Kelly A. Rigano, Editor(s)

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