Image Analysis Using Mathematical Morphology

For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided...

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Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 1987-07, Vol.PAMI-9 (4), p.532-550
Main Authors: Haralick, Robert M., Sternberg, Stanley R., Zhuang, Xinhua
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Closing
Computer architecture
Computer science
control theory
systems
Convolution
dilation
erosion
Exact sciences and technology
filtering
Image analysis
Image texture analysis
Logic arrays
Machine vision
Morphological operations
Morphology
opening
Pattern recognition. Digital image processing. Computational geometry
Robotic assembly
Shape
shape analysis
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Summary:For the purposes of object or defect identification required in industrial vision applications, the operations of mathematical morphology are more useful than the convolution operations employed in signal processing because the morphological operators relate directly to shape. The tutorial provided in this paper reviews both binary morphology and gray scale morphology, covering the operations of dilation, erosion, opening, and closing and their relations. Examples are given for each morphological concept and explanations are given for many of their interrelationships.
ISSN:0162-8828
1939-3539
DOI:10.1109/TPAMI.1987.4767941