Presentation is loading. Please wait.

Presentation is loading. Please wait.

Christopher Chedeau Gauthier Lemoine 1.  Algorithms ◦ Erosion & Dilation ◦ Opening & Closing ◦ Gradient ◦ Hit & Miss ◦ Thinning ◦ Top Hat ◦ Convolution.

PublishCamron Johnson Modified over 8 years ago

Similar presentations

Presentation on theme: "Christopher Chedeau Gauthier Lemoine 1.  Algorithms ◦ Erosion & Dilation ◦ Opening & Closing ◦ Gradient ◦ Hit & Miss ◦ Thinning ◦ Top Hat ◦ Convolution."— Presentation transcript:

1 Christopher Chedeau Gauthier Lemoine 1

2  Algorithms ◦ Erosion & Dilation ◦ Opening & Closing ◦ Gradient ◦ Hit & Miss ◦ Thinning ◦ Top Hat ◦ Convolution ◦ Reconstruction ◦ Watershed ◦ Min-Max Tree 2  Goals ◦ Segmentation ◦ Edge detection ◦ Skeletonization ◦ Image compression ◦ Noise reduction ◦ Feature Detection

3  Who ◦ Ecole des Mines – Paris ◦ Georges Matheron ◦ Jean Serra  Theories ◦ Set Theory (Binary) 70’s ◦ Lattice Theory (Grayscale) 80’s ◦ Topology 3  http://cmm.ensmp.fr/~serra/pdf/birth_of_mm.pdf http://cmm.ensmp.fr/~serra/pdf/birth_of_mm.pdf

4  http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf 4

5  http://www.imagemagick.org/Usage/morphology/ http://www.imagemagick.org/Usage/morphology/ 5

6  http://homepages.inf.ed.ac.uk/rbf/HIPR2/erode.htm http://homepages.inf.ed.ac.uk/rbf/HIPR2/erode.htm 6

7  http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf 7

8  http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf http://www2.ifi.auf.org/personnel/Alain.Boucher/cours/traitement_images/07-Images_binaires.pdf 8

9  http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf 9

10  http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf 10

11  http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf http://ia700307.us.archive.org/7/items/Lectures_on_Image_Processing/EECE253_18_GrayMorphology.pdf 11

12  http://cmm.ensmp.fr/~serra/cours/pdf/fr/ch3fr.pdf http://cmm.ensmp.fr/~serra/cours/pdf/fr/ch3fr.pdf 12

13  http://www.slideworld.org/viewslides.aspx/Introduction-to-Mathematical-Morphology-ppt-172551 http://www.slideworld.org/viewslides.aspx/Introduction-to-Mathematical-Morphology-ppt-172551 13

14  http://www.imagemagick.org/Usage/morphology/ http://www.imagemagick.org/Usage/morphology/ 14

15  http://www.imagemagick.org/Usage/morphology/ http://www.imagemagick.org/Usage/morphology/ 15

16  http://www.fmwconcepts.com/imagemagick/morphology/index.php http://www.fmwconcepts.com/imagemagick/morphology/index.php 16

17  http://www.mmorph.com/mxmorph/html/mmdemos/mmdpotatoes.html http://www.mmorph.com/mxmorph/html/mmdemos/mmdpotatoes.html 17

18  http://www.esiee.fr/~coupriem/Sdi_eng/squel.html http://www.esiee.fr/~coupriem/Sdi_eng/squel.html 18

19  http://manual.gimp.org/en/plug-in-convmatrix.html http://manual.gimp.org/en/plug-in-convmatrix.html Emboss Edge Detect Blur 19

20  http://en.wikipedia.org/wiki/Sobel_operator http://en.wikipedia.org/wiki/Sobel_operator 20

21  http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html 21

22  http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html 22

23  http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html http://www.mmorph.com/mmtutor1.0/html/mmtutor/mm060reconstruction.html 23

24  http://www.mmorph.com/mxmorph/html/mmdemos/mmdairport.html http://www.mmorph.com/mxmorph/html/mmdemos/mmdairport.html 24

25  http://cmm.ensmp.fr/~beucher/wtshed.html http://cmm.ensmp.fr/~beucher/wtshed.html With Markers 25

26  http://www.mmorph.com/mxmorph/html/mmdemos/mmdcalc.html http://www.mmorph.com/mxmorph/html/mmdemos/mmdcalc.html 26

27  http://www.nanobio.dk/assets/edge_detection.pdf http://www.nanobio.dk/assets/edge_detection.pdf 27

28  http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf 28

29  http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf http://gps-tsc.upc.es/imatge/pub/ps/IEEE_IP00_Salembier_Garrido.pdf 29

30  Simple Algorithms  Problem Specific Input  Process Chains 30

31 31

Download ppt "Christopher Chedeau Gauthier Lemoine 1.  Algorithms ◦ Erosion & Dilation ◦ Opening & Closing ◦ Gradient ◦ Hit & Miss ◦ Thinning ◦ Top Hat ◦ Convolution."

Similar presentations

OpenCV Introduction Hang Xiao Oct 26, 2012. History  1999 Jan : lanched by Intel, real time machine vision library for UI, optimized code for intel 

OpenCV Introduction Hang Xiao Oct 26, History  1999 Jan : lanched by Intel, real time machine vision library for UI, optimized code for intel 
Binary Image Analysis Selim Aksoy Department of Computer Engineering Bilkent University

Binary Image Analysis Selim Aksoy Department of Computer Engineering Bilkent University
Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.

Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.
Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.

Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.
CDS 301 Fall, 2009 Image Visualization Chap. 9 November 5, 2009 Jie Zhang Copyright ©

CDS 301 Fall, 2009 Image Visualization Chap. 9 November 5, 2009 Jie Zhang Copyright ©
Erlend Hodneland, University of Bergen Automated detection of TNT in cell images.

Erlend Hodneland, University of Bergen Automated detection of TNT in cell images.
Chapter 9: Morphological Image Processing

Chapter 9: Morphological Image Processing
Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.

Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.
Introduction to Morphological Operators

Introduction to Morphological Operators
Provides mathematical tools for shape analysis in both binary and grayscale images Chapter 13 – Mathematical Morphology Usages: (i)Image pre-processing.

Provides mathematical tools for shape analysis in both binary and grayscale images Chapter 13 – Mathematical Morphology Usages: (i)Image pre-processing.
Digital Image Processing, 2nd ed. www.imageprocessingbook.com © 2002 R. C. Gonzalez & R. E. Woods Chapter 9 Morphological Image Processing Chapter 9 Morphological.

Digital Image Processing, 2nd ed. © 2002 R. C. Gonzalez & R. E. Woods Chapter 9 Morphological Image Processing Chapter 9 Morphological.
Edge Detection Enhancement Using Gibbs Sampler

Edge Detection Enhancement Using Gibbs Sampler
Chapter 9 Morphological Image Processing. Preview Morphology: denotes a branch of biology that deals with the form and structure of animals and planets.

Chapter 9 Morphological Image Processing. Preview Morphology: denotes a branch of biology that deals with the form and structure of animals and planets.
Digital Image Processing Homework 4 TA. Yu-Lun Liu VC Lab. Dec.04, 2007.

Digital Image Processing Homework 4 TA. Yu-Lun Liu VC Lab. Dec.04, 2007.
SWE 423: Multimedia Systems Project #1: Image Segmentation Using Graph Theory.

SWE 423: Multimedia Systems Project #1: Image Segmentation Using Graph Theory.
1 © 2010 Cengage Learning Engineering. All Rights Reserved. 1 Introduction to Digital Image Processing with MATLAB ® Asia Edition McAndrew ‧ Wang ‧ Tseng.

1 © 2010 Cengage Learning Engineering. All Rights Reserved. 1 Introduction to Digital Image Processing with MATLAB ® Asia Edition McAndrew ‧ Wang ‧ Tseng.
Feature extraction Feature extraction involves finding features of the segmented image. Usually performed on a binary image produced from.

Feature extraction Feature extraction involves finding features of the segmented image. Usually performed on a binary image produced from.
Brief overview of ideas In this introductory lecture I will show short explanations of basic image processing methods In next lectures we will go into.

Brief overview of ideas In this introductory lecture I will show short explanations of basic image processing methods In next lectures we will go into.
Image Segmentation and Registration Rachel Jiang Department of Computer Science Ryerson University 2006.

Image Segmentation and Registration Rachel Jiang Department of Computer Science Ryerson University 2006.
Lecture 5. Morphological Image Processing. 10/6/20152 Introduction ► ► Morphology: a branch of biology that deals with the form and structure of animals.

Lecture 5. Morphological Image Processing. 10/6/20152 Introduction ► ► Morphology: a branch of biology that deals with the form and structure of animals.

Similar presentations

Ads by Google