Morphological Correlation for Robust Image Recognition

In literature several correlation filters have been proposed for image recognition. Traditionally linear correlation is applied among the images for this purpose, however, the operation is not robust when images are corrupted with non-Gaussian noise. In this paper we propose the use of morphological correlation combined with nonlinear filters for robust image recognition. Performance of the proposed technique is compared with that of classical linear filtering in terms of discrimination capability. Computer simulation results are provided and discussed.