Developing morphological building blocks: from design to implementation

Mathematical morphology has become a widely-used technique for image processing and computer vision. Initially designed as a set theory, it was generalized to the set of gray-scale images and to the complete lattice framework. Despite this accredited theoretical evolution, contemporary practice in morphological algorithm development still lacks a standardized, mathematically rigorous algebraic structure that is specifically designed for image handling. The purpose of this paper is twofold: first, it is intended to give rise to a new morphological framework that overcomes the combinatorial explosion of algorithms needed to deal with all possible types of lattices and structuring functions. Second, it provides us with the essential tools to design and implement generic building blocks for morphological image operators