Detection of minelike targets using grayscale morphological image reconstruction

Ashish Banerji; John Ioannis Goutsias

doi:10.1117/12.211377

20 June 1995 Detection of minelike targets using grayscale morphological image reconstruction

Ashish Banerji, John Ioannis Goutsias

Proceedings Volume 2496, Detection Technologies for Mines and Minelike Targets; (1995) https://doi.org/10.1117/12.211377
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

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.

Citation Download Citation

Ashish Banerji and John Ioannis Goutsias "Detection of minelike targets using grayscale morphological image reconstruction", Proc. SPIE 2496, Detection Technologies for Mines and Minelike Targets, (20 June 1995); https://doi.org/10.1117/12.211377

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