SlideShare a Scribd company logo
Digital Geometry and Image Processing
Dietmar Saupe
Course Outline
SS 2006
Digital Geometry and Image
Processing (3V+2Ü)
 Geometric methods for digital picture analysis
 Scope: Graduate course
 Information Engineering master and PhD students
 Classes (Vorlesung), D. Saupe
 Tuesdays 8:15h-11h, Z714 (preliminary)
 Problem sessions (Übg.), V. Bondarenko
 Thursdays 14:00h-15:30h, Z714 (preliminary)
Primary course text book
 Reinhard Klette,
Azriel Rosenfeld
 Digital Geometry
 Morgan Kaufmann
(Elsevier) 2004
 UB will have copies
Secondary course text book
 R.C. Gonzales, R.E. Woods
 Digital Image Processing
 Prentice-Hall (2nd Ed.) 2002
 3rd edition
 UB has copies
Digital Geometry
Geometric methods for digital picture analysis
 Focus is on digital image or picture
analysis
 Core of the field
 Related mathematical fundamenals
 It is not
 yet another treatment of a very broad range
of problems, algorithms, heuristics, and
„useful“ technologies
Introduction
Color images (pictures)
 An RGB picture
 Its 3 color channels
 Histograms
Introduction
Early digital pictures
 A Greek pebble mosaic, detail from
“The Lion Hunt” in Pella,Macedonia,
circa 300 BC.
 Pattern woven by a Jacquard loom: a
black-and-white silk portrait of Jacquard
himself, woven under the control of a
“program” consisting of about 24,000
cards (one is shown on the left).
Early 19th century, before Babbage!
Introduction
Digital pictures in 2005
 Standard 16 Megapixel CCD cameras evolving
 Specialized cameras in photogrammetry of 100 Megapixels
 3D imaging modalities (CT, MRI, ...)
 3D-laser range scanners
 Leon Harmon of Bell Labs: picture of
Lincoln (252 pixels), “The Recognition
of Faces”, Scientific American, (Nov. 1973).
 A 380 degree panoramic picture of Auckland,
New Zealand, 2002,
500 Megapixels
Introduction
Grid of squares versus grid of points
 Two concepts for pixels (cells)
 Is the value a component of the pixel?
 A picture P is a mapping of a finite
rectangular grid region into the reals
 Generalization to 3D: voxel
Introduction
Adjacency
 Version 1
 Cell 1-adjacency and pixel 4-adjacency (left)
 Neighborhoods (right)
 Version 2
 Cell 0-adjacency and pixel 8-adjacency (left)
 Neighborhoods (right)
 In 3D:
 Cells? Voxels?
Introduction
Replace the X´s!
 Top:
 X-adjacent cells
 X-adjacent pixels
 Bottom:
 X-adjacent cells
 X-adjacent pixels
Introduction
Same in 3D!
 X-adjacent 3-cells :
 X= ? (left, middle, right)
 X-adjacent voxels :
 X= ? (left, right)
Introduction
Grid point connectivity
 Points are 4-connected? 8-connected?
 Background 4-connected? 8-connected?
Introduction
Equivalent classes
 Equivalence relation R on finite grid
 Reflexive, symmetric, transitive
 Yields equivalence classes
 For a picture P-equivalence:
 Pixels p,q: pRq iff P(p)=P(q)
Introduction
Component labelling
 Assume 4-adjacency of pixels
 Frequent task: label the 4-connected
components of the equivalence classes
 Some algorithms
 Fill algorithm:
 Rosenfeld-Pfaltz
labelling scheme
Introduction
Image scan sequences
 Examples:
 Space filling curves (Peano, Hilbert)
Topics (Chapters)
Metrics
 Basics: Norms, Minkowski metrics, integer valued
metrics, induced topology, Hausdorff metric
 Grid point metrics, paths, geodesics, intrinsic distances
 Metrics on pictures:
distance transforms
 medial axis
Topics (Chapters)
Adjacency graphs
 Graphs and connectedness, basic graph theory, Euler
characteristic and planarity
 Boundaries, cycles, frontiers in incidence pseudographs
 Inner (gray) pixel
border (black) pixel
co-border (gray) pixel
Topics (Chapters)
Topology
 Topological spaces, digital topologies
 Concepts homeomorphy, isotopy (top.
equivalence)
 Simplicial complexes, triangulations
Topics (Chapters)
Curves and surfaces: topology, geometry
 Jordan curves, curves in grids
 Surfaces and manifolds, ... in 3D grids
 Arc length, curvature, angles, areas
 Surfaces and solids
 Principal, gaussian, mean curvature
 Tracing surfaces
Topics (Chapters)
Curves and surfaces in grids
 Straightness, 2D and 3D
 Measuring arc length, curvature, corners
 Digital planes
 Measuring surface area, curvature
Selected Topics
 Moments and their estimation
 Other picture properties
 Spatial relations
Selected Topics (not covered)
 Hulls and diagrams (convexity, Voronoi)
 Transformations (t. groups, symmetries,
magnification, ...)
 Morphological operators (dilation, erosion,
simplification, segmentation, ...)
 Deformations (topological-preserving def.,
shrinking, thinning, ...)

More Related Content

PDF
PDF
Biomedical engineering 20230918-Fundamentals.pdf
PDF
2. IP Fundamentals.pdf
PPT
digital image processing chapter two, fundamentals
PPT
Image_Processing-ch2surface r_part_2.ppt
PPT
Image processing 1-lectures
PPT
03 digital image fundamentals DIP
PDF
Digital geometry an introduction
Biomedical engineering 20230918-Fundamentals.pdf
2. IP Fundamentals.pdf
digital image processing chapter two, fundamentals
Image_Processing-ch2surface r_part_2.ppt
Image processing 1-lectures
03 digital image fundamentals DIP
Digital geometry an introduction

Similar to DigitalGeometry.ppt (20)

PDF
Digital geometry - An introduction
PPTX
Digital-Image-processing-fundamenntal.pptx
PPTX
Digital Image Processing Unit 2 ppt.pptx
PDF
Manuscript document digitalization and recognition: a first approach
PPTX
computer Vision and Machine learning Chapter 1
PPTX
Topic 1- computer vision and machine learning
PPT
Digital Image Fundamentals 1.ppt
PDF
Computer Graphics Notes.pdf
PDF
Cliff sugerman
PPTX
Machine Perception with cognition
PPT
chap2.ppt
PPT
pixelrelationships-m-1.pptx.ppt
PDF
PDF
Computer graphics lecturenotes_torontouniv
PPTX
3D Graphics : Computer Graphics Fundamentals
PDF
CVPR 2012 Review Seminar - Multi-View Hair Capture using Orientation Fields
PDF
Mesh Processing Course : Introduction
PDF
Digital image processing fundamental explanation
PPTX
3D-Object Representation in Computer Graphics.pptx
PDF
Ip unit 1
Digital geometry - An introduction
Digital-Image-processing-fundamenntal.pptx
Digital Image Processing Unit 2 ppt.pptx
Manuscript document digitalization and recognition: a first approach
computer Vision and Machine learning Chapter 1
Topic 1- computer vision and machine learning
Digital Image Fundamentals 1.ppt
Computer Graphics Notes.pdf
Cliff sugerman
Machine Perception with cognition
chap2.ppt
pixelrelationships-m-1.pptx.ppt
Computer graphics lecturenotes_torontouniv
3D Graphics : Computer Graphics Fundamentals
CVPR 2012 Review Seminar - Multi-View Hair Capture using Orientation Fields
Mesh Processing Course : Introduction
Digital image processing fundamental explanation
3D-Object Representation in Computer Graphics.pptx
Ip unit 1
Ad

Recently uploaded (20)

PDF
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
PPT
Project quality management in manufacturing
PDF
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
PPTX
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx
PDF
composite construction of structures.pdf
PPTX
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
PPTX
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
PPTX
Foundation to blockchain - A guide to Blockchain Tech
PPTX
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
PDF
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
PDF
Digital Logic Computer Design lecture notes
PDF
Embodied AI: Ushering in the Next Era of Intelligent Systems
PPT
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
PDF
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
PPTX
KTU 2019 -S7-MCN 401 MODULE 2-VINAY.pptx
PPTX
Geodesy 1.pptx...............................................
PDF
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
PDF
Model Code of Practice - Construction Work - 21102022 .pdf
PPTX
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
PDF
R24 SURVEYING LAB MANUAL for civil enggi
Mohammad Mahdi Farshadian CV - Prospective PhD Student 2026
Project quality management in manufacturing
keyrequirementskkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkkk
MCN 401 KTU-2019-PPE KITS-MODULE 2.pptx
composite construction of structures.pdf
M Tech Sem 1 Civil Engineering Environmental Sciences.pptx
Engineering Ethics, Safety and Environment [Autosaved] (1).pptx
Foundation to blockchain - A guide to Blockchain Tech
Infosys Presentation by1.Riyan Bagwan 2.Samadhan Naiknavare 3.Gaurav Shinde 4...
The CXO Playbook 2025 – Future-Ready Strategies for C-Suite Leaders Cerebrai...
Digital Logic Computer Design lecture notes
Embodied AI: Ushering in the Next Era of Intelligent Systems
CRASH COURSE IN ALTERNATIVE PLUMBING CLASS
Evaluating the Democratization of the Turkish Armed Forces from a Normative P...
KTU 2019 -S7-MCN 401 MODULE 2-VINAY.pptx
Geodesy 1.pptx...............................................
July 2025 - Top 10 Read Articles in International Journal of Software Enginee...
Model Code of Practice - Construction Work - 21102022 .pdf
FINAL REVIEW FOR COPD DIANOSIS FOR PULMONARY DISEASE.pptx
R24 SURVEYING LAB MANUAL for civil enggi
Ad

DigitalGeometry.ppt

  • 1. Digital Geometry and Image Processing Dietmar Saupe Course Outline SS 2006
  • 2. Digital Geometry and Image Processing (3V+2Ü)  Geometric methods for digital picture analysis  Scope: Graduate course  Information Engineering master and PhD students  Classes (Vorlesung), D. Saupe  Tuesdays 8:15h-11h, Z714 (preliminary)  Problem sessions (Übg.), V. Bondarenko  Thursdays 14:00h-15:30h, Z714 (preliminary)
  • 3. Primary course text book  Reinhard Klette, Azriel Rosenfeld  Digital Geometry  Morgan Kaufmann (Elsevier) 2004  UB will have copies
  • 4. Secondary course text book  R.C. Gonzales, R.E. Woods  Digital Image Processing  Prentice-Hall (2nd Ed.) 2002  3rd edition  UB has copies
  • 5. Digital Geometry Geometric methods for digital picture analysis  Focus is on digital image or picture analysis  Core of the field  Related mathematical fundamenals  It is not  yet another treatment of a very broad range of problems, algorithms, heuristics, and „useful“ technologies
  • 6. Introduction Color images (pictures)  An RGB picture  Its 3 color channels  Histograms
  • 7. Introduction Early digital pictures  A Greek pebble mosaic, detail from “The Lion Hunt” in Pella,Macedonia, circa 300 BC.  Pattern woven by a Jacquard loom: a black-and-white silk portrait of Jacquard himself, woven under the control of a “program” consisting of about 24,000 cards (one is shown on the left). Early 19th century, before Babbage!
  • 8. Introduction Digital pictures in 2005  Standard 16 Megapixel CCD cameras evolving  Specialized cameras in photogrammetry of 100 Megapixels  3D imaging modalities (CT, MRI, ...)  3D-laser range scanners  Leon Harmon of Bell Labs: picture of Lincoln (252 pixels), “The Recognition of Faces”, Scientific American, (Nov. 1973).  A 380 degree panoramic picture of Auckland, New Zealand, 2002, 500 Megapixels
  • 9. Introduction Grid of squares versus grid of points  Two concepts for pixels (cells)  Is the value a component of the pixel?  A picture P is a mapping of a finite rectangular grid region into the reals  Generalization to 3D: voxel
  • 10. Introduction Adjacency  Version 1  Cell 1-adjacency and pixel 4-adjacency (left)  Neighborhoods (right)  Version 2  Cell 0-adjacency and pixel 8-adjacency (left)  Neighborhoods (right)  In 3D:  Cells? Voxels?
  • 11. Introduction Replace the X´s!  Top:  X-adjacent cells  X-adjacent pixels  Bottom:  X-adjacent cells  X-adjacent pixels
  • 12. Introduction Same in 3D!  X-adjacent 3-cells :  X= ? (left, middle, right)  X-adjacent voxels :  X= ? (left, right)
  • 13. Introduction Grid point connectivity  Points are 4-connected? 8-connected?  Background 4-connected? 8-connected?
  • 14. Introduction Equivalent classes  Equivalence relation R on finite grid  Reflexive, symmetric, transitive  Yields equivalence classes  For a picture P-equivalence:  Pixels p,q: pRq iff P(p)=P(q)
  • 15. Introduction Component labelling  Assume 4-adjacency of pixels  Frequent task: label the 4-connected components of the equivalence classes  Some algorithms  Fill algorithm:  Rosenfeld-Pfaltz labelling scheme
  • 16. Introduction Image scan sequences  Examples:  Space filling curves (Peano, Hilbert)
  • 17. Topics (Chapters) Metrics  Basics: Norms, Minkowski metrics, integer valued metrics, induced topology, Hausdorff metric  Grid point metrics, paths, geodesics, intrinsic distances  Metrics on pictures: distance transforms  medial axis
  • 18. Topics (Chapters) Adjacency graphs  Graphs and connectedness, basic graph theory, Euler characteristic and planarity  Boundaries, cycles, frontiers in incidence pseudographs  Inner (gray) pixel border (black) pixel co-border (gray) pixel
  • 19. Topics (Chapters) Topology  Topological spaces, digital topologies  Concepts homeomorphy, isotopy (top. equivalence)  Simplicial complexes, triangulations
  • 20. Topics (Chapters) Curves and surfaces: topology, geometry  Jordan curves, curves in grids  Surfaces and manifolds, ... in 3D grids  Arc length, curvature, angles, areas  Surfaces and solids  Principal, gaussian, mean curvature  Tracing surfaces
  • 21. Topics (Chapters) Curves and surfaces in grids  Straightness, 2D and 3D  Measuring arc length, curvature, corners  Digital planes  Measuring surface area, curvature
  • 22. Selected Topics  Moments and their estimation  Other picture properties  Spatial relations
  • 23. Selected Topics (not covered)  Hulls and diagrams (convexity, Voronoi)  Transformations (t. groups, symmetries, magnification, ...)  Morphological operators (dilation, erosion, simplification, segmentation, ...)  Deformations (topological-preserving def., shrinking, thinning, ...)