A fuzzy shell clustering approach to recognize hyperbolic signatures in subsurface radar images

Abstract

The authors propose a pattern recognition approach to analyze subsurface radar images and recognize the hyperbolic signatures produced by targets. After enhancing these signatures using a wavelet denoising procedure, pixels are grouped into significant hyperbolic shapes by fuzzy clustering. The approach also provides a validation measure for each recognized shape using so-called "shell thickness". Excellent experimental results justify the use of this algorithm for automatic interpretation of subsurface radar images.