Abstract
Mathematical morphology (MM) or simply morphology can be defined as a theory for the analysis of spatial structures. It is called morphology because it aims at analysing the shape and form of objects. It is mathematical in the sense that the analysis is based on set theory, integral geometry, and lattice algebra. MM is not only a theory, but also a powerful image analysis technique. The purpose of this book is to provide a detailed presentation of the principles and applications of morphological image analysis. The emphasis is therefore put on the technique rather than the theory underlying MM. Besides, any non-specialist faced with an image analysis problem rapidly realises that a unique image transformation usually fails to solve it. Indeed, most image analysis problems are very complex and can only possibly be solved by a combination of many elementary transformations. In this context, knowledge of the individual image processing operators is a necessary but not sufficient condition to find a solution: guidelines and expert knowledge on the way to combine the elementary transformations are also required. Hence, beyond the presentation of the morphological operators, we will describe many real applications to help the reader acquiring the expert knowledge necessary for building the chain of operators to resolve his/her own image analysis problem.
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Bibliographical notes and references
Batchelor, B., Whelan, P. (1997), Intelligent vision systems for industry, Springer-Verlag, London.
Batchelor, B., Hill, D., Hodgson, D., eds (1985), Automated visual inspection, IFS (Publications) Ltd, UK.
Beucher, S., Lantuéjoul, C. (1979), Use of watersheds in contour detection, in ‘International Workshop on Image Processing’, CCETT/IRISA, Rennes.
Davies, E. (1996), Machine Vision: Theory, Algorithms, and Practicalities,2nd edii, Academic Press.
Digabel, H., Lantuéjoul, C. (1978), Iterative algorithms, in J.-L. Chermant, ed., ‘Quantitative analysis of microstructures in materials sciences, biology and medicine’, Dr. Riederer-Verlag GmbH, Stuttgart, pp. 85–99.
Gonzalez, R., Wintz, P. (1987), Digital image processing, 2nd edn, Addison-Wesley, Reading, MA.
Haralick, R., Shapiro, R. ( 1992 1993), Computer and Robot Vision, Vols. 1, 2, Addison-Wesley, Reading, MA.
Heijmans, H. (1994), Morphological image operators, Advances in Electronics and Electron Physics, Academic Press.
Heijmans, H. (1995), ‘Mathematical morphology: a modern approach in image processing based on algebra and geometry’, SIAM Review 37 (1), 1–36.
Jähne, B. (1997), Digital Image Processing, 4th edn, Springer-Verlag, Berlin.
Jähne, B., Haußecker, H., Geißler, P., eds (1999), Handbook of Computer Vision and Applications, Vols. I—III, Academic Press.
Jain, A. (1989), Fundamentals of Digital Image Processing, Prentice Hall, Englewood Cliffs.
Klein, J.-C., Serra, J. (1972), ‘The texture analyser’, Journal of Microscopy 95, 349–356.
Klette, R., Zamperoni, P. (1996), Handbook of image processing operators, John Wiley Sons, Chichester.
Matheron, G. (1967), Eléments pour une théorie des milieux poreux, Masson, Paris.
Matheron, G. (1975), Random sets and integral geometry,Wiley.
Rosenfeld, A., Kak, A. (1982), Digital Picture Processing, Vols. I—II, 2nd edn, Academic Press, Orlando.
Serra, J. (1982), Image analysis and mathematical morphology, Academic Press, London.
Serra, J. (1994), The “Centre de Morphologie Mathématique”: an overview, in J. Serra, P. Soille, eds, ‘Mathematical morphology and its applications to image processing’, Kluwer Academic Publishers, pp. 369–374.
Serra, J., ed. (1988), Image analysis and mathematical morphology. Volume 2: theoretical advances, Academic Press, London.
Sonka, M., Hlavâc, V., Boyle, R. (1994), Image Processing, Analysis and Machine Vision, Chapman and Hall Computing.
Vernon, D. (1991), Machine Vision, Prentice Hall, Englewood Cliffs.
Vincent, L., Soille, P. (1991), ‘Watersheds in digital spaces: an efficient algorithm based on immersion simulations’, IEEE Transactions on Pattern Analysis and Machine Intelligence 13 (6), 583–598.
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© 1999 Springer-Verlag Berlin Heidelberg
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Soille, P. (1999). Introduction. In: Morphological Image Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03939-7_1
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DOI: https://doi.org/10.1007/978-3-662-03939-7_1
Publisher Name: Springer, Berlin, Heidelberg
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