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Image Analysis Using Mathematical Morphology

IEEE Transactions on Pattern Analysis and Machine Intelligence · 1987 · Vol. PAMI-9(4) · pp. 532–550
Robert M. HaralickS. SternbergXinhua Zhuang

Abstract

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.

Image and Object Detection TechniquesMedical Image Segmentation TechniquesIndustrial Vision Systems and Defect DetectionMathematical morphologyDilation (metric space)Computer scienceArtificial intelligenceClosing (real estate)Morphological gradientImage processingGrayscaleStructuring elementConvolution (computer science)
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References
Design of a Massively Parallel Processor
IEEE Transactions on Computers · 1980 · 700 citations
Image Analysis and Mathematical Morphology.
Biometrics · 1983 · 3,907 citations
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