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Multiple-aspect Fixed-Range Template Matching for the detection and classification of underwater unexploded ordnance in DIDSON sonar images

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3 Author(s)
Brisson, L.N. ; Dept. of Ocean & Mech. Eng., Florida Atlantic Univ., Dania Beach, FL, USA ; Beaujean, P.-P. ; Negahdaripour, S.

This paper presents a sonar specific methodology to detect and classify underwater unexploded ordnance (UXO) in the low resolution sonar data captured by the DIDSON US300. This technique, known as the Multiple-Aspect Fixed-Range Template Matching (MAFR-TM) algorithm, is designed to detect and classify a target of high characteristic impedance in an environment that contains similar shaped objects of low characteristic impedance. The MAFR-TM is based on the proven concept of template matching, which is a two-dimensional correlation between a reference image (template) and an image collected during field operations (source image). In the MAFR-TM algorithm, the template matching method is efficiently implemented in the wave number domain using two-dimensional Fast Fourier Transforms (2D-FFT) and wave number leakage is reduced with an optimized separable two-dimensional Kaiser window. Experimental results are provided to demonstrate the performance of the proposed approach.

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Date of Conference:

20-23 Sept. 2010