From binary to grey tone image processing using fuzzy logic concepts

摘要

The concept of fuzzy logic was introduced by Zadeh in 1965 as a tool for analysing complex systems and decision processes. In fuzzy set theory, the binary Boolean operations of OR and AND generalise to the min and max functions. Nakagawa(8) later introduced the idea of local min and max operators to image processing as the grey equivalents to the parallel binary operations of shrinking and expanding. In this paper the ideas of min and max are further investigated and their usefulness in image processing assessed by extending some already well known binary processes into grey level algorithms. The functions of minπ and maxπ are introduced (deleted neighbourhood minπ and maxπ) as the analogues of nearest neighbour “propagation” signals of binary images. Examples of grey edge detection, spatial filtering, object labelling and grey thinning algorithms are given.