An introduction to image processing in addition to explaining the concept of group operations. Find me on: AFCIT http://www.afcit.xyz YouTube https://www.youtube.com/channel/UCuewOYbBXH5gwhfOrQOZOdw Google Plus https://plus.google.com/u/0/+AhmedGadIT SlideShare https://www.slideshare.net/AhmedGadFCIT LinkedIn https://www.linkedin.com/in/ahmedfgad/ ResearchGate https://www.researchgate.net/profile/Ahmed_Gad13 Academia https://www.academia.edu/ Google Scholar https://scholar.google.com.eg/citations?user=r07tjocAAAAJ&hl=en Mendelay https://www.mendeley.com/profiles/ahmed-gad12/ ORCID https://orcid.org/0000-0003-1978-8574 StackOverFlow http://stackoverflow.com/users/5426539/ahmed-gad Twitter https://twitter.com/ahmedfgad Facebook https://www.facebook.com/ahmed.f.gadd Pinterest https://www.pinterest.com/ahmedfgad/

1. Image Processing

2. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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3. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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4. HVS – Eye Structure
Eye has 3 basic
membranes.
1. Cornea
2. Choroid
3. Retina
Retina is the
membrane of
interest.
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5. Retina
• Light sensitive layer at the back of the eye.
• Retina has photoreceptor cells called cones and rods.
• Cones and rods convert light energy into signal to
human brain via optic nerve.
Light Retina Brain
Light to
Signal Image
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6. Fovea : Cons and Rods
• Fovea is the central location in retina.
• Cones in one eye range from 6 to 7 million.
• Rods range between 75 to 120 million.
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7. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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8. Digital Camera
• Think of fovea as an array of photoreceptors
(cones and rods).
• Digital camera works like human eye.
• Has a number of photoreceptors forming charge-
coupled device (CCD) array of pixels.
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9. Sampling and Quantization
• Sampling is a process of digitizing coordinate values.
• Quantization is a process of digitizing amplitude values.
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10. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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11. What is an Image?
• 2D function f(x,y)
• x and y are spatial coordinates
• F(x,y) intensity at (x,y)
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12. Color Models
• Provides different ways to represent a color to be
suitable for different applications.
RGB(255,0,0)
CMYK(0,255,255,0)
HSV(0,255,255)
RED
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13. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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14. Image Processing
Input
Image
Output
Image
Processing
Feature
Vector
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15. Image Processing
Operations
Point Operations
Group Operations
Template + Operation
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16. Template
• Template or a mask is used to specify which pixels will
join current operation.
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17. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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18. General Filter
Template Convolution
• Image-template multiplication and may be of different
sizes.
58 3 213 81 78
185 87 32 27 11
71 66 60 2 19
61 91 129 89 38
14 7 58 14 42
0 0 0 0 00
0
0
0
0
0
0
0
0
0
0
0
0 0 0 0 0 0 0
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19. Averaging Filter
• Advantages : low-pass filter that removes noise and
smooth image
• Disadvantages : Cause blurring and reduce image
details.
• The larger the template the more noise removed and
more details lost.
1/9 1/9 1/9
1/9 1/9 1/9
1/9 1/9 1/9
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20. Average Filter
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21. Gaussian Averaging Filter
• Remove noise but retains image details.
• It uses the Gaussian function to generate the template
values
(1,1) (0,1) (1,1)
(1,0) (0,0) (1,0)
(1,1) (0,1) (1,1)
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22. 11/11/2015 22

23. Median Filter
66
58 3 213 81 78
185 87 32 27 11
71 66 60 2 19
61 91 129 89 38
14 7 58 14 42
58 3 213
185 87 32
71 66 60
3 32 58 60 66 71 87 185 213
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24. Alternative Templates
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25. Median Filter
• Used to remove salt and pepper
noise that may arise from decoding
errors in picture transmission systems.
• The salt and pepper noise points will
appear at either end of the rank
ordered list and are removed by the
median process.
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26. Median Filter
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27. Index
• Human Visual System (HVS)
o Eye structure
• Eye Membranes
• Retina
• Fovea (Cones and Rods)
• Digital Camera
o Charge-Coupled Device (CCD)
o Image Sampling and Quantization
• Digital Image
o What is an Image?
o Color Models/Systems
• Image Processing
o Image Processing Operations
• Point Operations
• Group Operations
o Filters
• Averaging Filter
• Gaussian Filter
• Median Filter
o Morphological Operations
• Dilation
• Erosion
• Opening
• Closing
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28. Morphological Operations
• Applied to binary images and may be applied
to gray images.
• Goal is to extract specific structures from
the image.
• Two primitive Morphological operations are
o Dilation
o Erosion
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29. Structured Element
• Shape used to search for a specific structure in the
image.
• Major step in morphological operations is to extract the
appropriate structured element.
• Selection of the appropriate structured element is based
on the application at hand.
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30. Dilation
• Referred to as IM ⊕ SE
• Enlarge the boundaries of foreground regions.
IM ∪ SE
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31. Dilation
• Enlarge the boundaries of foreground regions.
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32. Dilation
• Enlarge the boundaries of foreground regions.
IM ∪ SE
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33. Dilation
• Enlarge the boundaries of foreground regions.
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34. Dilation
• Enlarge the boundaries of foreground regions.
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35. Dilation Results
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36. Erosion
• Referred to as IM ⊝ SE
• Erode away the boundaries of foreground regions.
IM ∩ SE
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37. Erosion
• Erode away the boundaries of foreground regions.
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38. Erosion
• Erode away the boundaries of foreground regions.
IM ∩ SE
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39. Erosion
• Erode away the boundaries of foreground regions.
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40. Erosion Results
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41. Opening
• IM SE= (IM ⊝ SE)⊕ SE
• Remove foreground edges but
less destructive than erosion.
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42. Closing
• IM SE = (IM ⊕ SE) ⊝ SE
• Enlarge foreground edges but
less destructive than dilation.
11/11/2015 42

43. Morphological Operations
Applications – Noise Removal
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44. Morphological Operations
Applications – Edge Detection
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45. Morphological Operations
Applications – Object Extraction
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