MORPHOLOGICAL OPENING AND CLOSING NEURAL NETWORKS FOR IMAGE FILTERING
图像滤波的形态学开、闭型神经网络算法

This paper presents morphological neural networks of opening and closing operation for pratical use, and the algorithm to design optimal parameters of a morphological filter, Experimental results show that this method is good in practice and easy to extend. It has better filtering properties than that of the conventional morphological ones. The task of creating a morphological filter can be divided into two basic problems, selecting a morphological operation and Structuring Element (SE). The set of morphological operations is predefined so the filter's properties depend merely on the selection of an SE. Structuring elements are formed by means of an adaptive algorithm that adjust the shape of the SE to match characteristics of the image targets. Morphological filters formed using this method are capable of responding complicated patterns in images.