Genetic training algorithm for morphological filters
Yu Nong, Li Yushu, Xu Qifu · 2002
It is widely accepted that the design of morphological filters which are optimal in some sense is a difficult task. We propose a new method which is the genetic training algorithm for morphological filters (GTAMF). The GTAMF incorporates two new operators of crossover and mutation called curved cylinder crossover and master-slave mutation. Experimental results show that this method is good in practice and easy to extend. Morphological filters formed by this method are capable of responding complicated patterns in images.