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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.

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