Image enhancement using mathematical morphology with adaptive structuring elements

Mathematical morphology has been widely used in recent years in the image processing area. Due to the nonlinear nature of morphological operations, their application to some image noise removal problems have achieved very impressive results. However, of the morphological algorithms by far most use only a single structuring element. To optimize the performances on various parts of an image, we introduce morphological operations using an adaptive structuring element for noise removal of binary and grayscale images. These techniques were used in the preprocessing of character recognition problems at CEDAR, SUNY at Buffalo, New York. Demonstrations of the improved performance of the algorithm are provided.