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Mathematical morphology for analysing soil structure from images
Author(s) -
Horgan
Publication year - 1998
Publication title -
european journal of soil science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.244
H-Index - 111
eISSN - 1365-2389
pISSN - 1351-0754
DOI - 10.1046/j.1365-2389.1998.00160.x
Subject(s) - mathematical morphology , set (abstract data type) , scale (ratio) , sampling (signal processing) , replication (statistics) , computer science , noise (video) , image (mathematics) , resolution (logic) , binary number , morphology (biology) , algorithm , biological system , mathematics , image processing , artificial intelligence , computer vision , geology , statistics , cartography , geography , arithmetic , filter (signal processing) , paleontology , biology , programming language
Mathematical morphology is an approach to image analysis based on set theory. It explores structures by examining the effect of transforming them by set operations. Such operations can be built up and combined into powerful tools for exploring, transforming and measuring the size, shape and connectivity of components of interest in images. Greylevel images are handled by regarding them as binary images in three dimensions. This paper reviews the basic ideas and illustrates them by application to studies of the size distribution of soil pores, the lengths and geometric patterns of cracks in drying soil, and the growth of fungal hyphae. It then extends them in an introductory way to random sets. Practical issues of scale, resolution, sampling, replication and noise in the use of images for soil measurement are described briefly.