Morphological Image Processing
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Morphological Image Processing
Preechaya Srisombut
Graduate School of Information Sciences and Engineering,Tokyo Institute of Technology
For IP seminar, 4 November 2004
Reference: Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing,” Second Edition,
Prentice Hall, p.519-560&617-621
Contents:
1. Introduction
2. Preliminaries
• Basic Concepts from Set Theory
• Logic Operations
3. Morphological Operations
• Dilation and Erosion
• Opening and Closing
• The Hit-or-Miss Transformation
4. Basic Morphological Algorithms
• Boundary Extraction
• Region Filling
• Extraction of Connected Components
• Convex Hull
• Thinning
• Thickening
• Pruning
5. Extensions to Gray-Scale Images
• Dilation, Erosion, Opening, and Closing
6. Some Applications of Gray-Scale
Morphology
• Morphological smoothing
• Morphological gradient
• Top-hat transformation
• Textural segmentation
• Granulometry
7. Summary
Appendix: Summary of Morphological Operations
on Binary Images
1. Introduction
Morphology commonly denotes a branch of biology
that deals with the form and structure of animals and
plants.
Here, the same word morphology is used as a tool
for extracting image components that are useful in the
representation and description of region shape. It is
also used for pre- or post processing, such as filtering.
The language of mathematical morphology use set
theory to represent objects in an image.
2. Preliminaries
• Basic Concepts from Set Theory
For binary image, let A be a set in Z
2
a ∈ A； a = (a1, a2) is an element of A.
Set Operations:
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