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Introduction to Introduction to Morphological Morphological
OperatorsOperators
Apr 18, 2023 1
About this lecture
• In this lecture we introduce INFORMALLY the most important operations based on morphology, just to give you the intuitive feeling.
• In next lectures we will introduce more formalism and more examples.
04/18/23 2
EROSIONEROSION
04/18/23 3
What We Do Today. 2nd Part
• Introduction to Morphological Operators
– Used generally on binary images, e.g., background subtraction results!
– Used on gray value images, if viewed as a stack to binary images.
• Good for, e.g.,– Noise removal in background
– Removal of holes in foreground / background
• Check: www.cee.hw.ac.uk/hipr
A first Example: Erosion• Erosion is an important morphological
operation
• Applied Structuring Element:
Apr 18, 2023 5
Example for Erosion
Apr 18, 2023 6
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0Output Image
111
Example for Erosion
Apr 18, 2023 7
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0Output Image
111
Example for Erosion
Apr 18, 2023 8
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0Output Image
111
Example for Erosion
Apr 18, 2023 9
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0 0Output Image
111
Example for Erosion
Apr 18, 2023 10
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0 0 1Output Image
111
Example for Erosion
Apr 18, 2023 11
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0 0 1 0Output Image
111
Example for Erosion
Apr 18, 2023 12
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0 0 1 0 0Output Image
111
Example for Erosion
Apr 18, 2023 13
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
0 0 0 0 1 0 0 0Output Image
111
Introduction
• Structuring Element• Erosion• Dilation• Opening• Closing• Outlook: Hit-and-miss Operation, Thinning,
Thickening
Apr 18, 2023 14
Structuring Element (Kernel)• Structuring Elements can have varying sizes• Usually, element values are 0,1 and none(!)• Structural Elements have an origin• For thinning, other values are possible• Empty spots in the Structuring Elements are don’t
care’s!
Apr 18, 2023 15
Box
Disc
Examples of stucturing elements
Dilation & Erosion
• Basic operations
• Are dual to each other:– ErosionErosion shrinks foreground, enlarges
Background
– Dilation enlarges foreground, shrinks background
Apr 18, 2023 16
Erosion
• Erosion is the set of all points in the image, where the structuring element “fits into”.
• Consider each foreground pixel in the input image– If the structuring element fits in, write a “1” at the
origin of the structuring element!
• Simple application of pattern matching• Input:
– Binary Image (Gray value)– Structuring Element, containing only 1s!
Apr 18, 2023 17
Another example of erosion
• White = 0, black = 1, dual property, image as a result of erosion gets darker
Apr 18, 2023 18
Erosion on Gray Value Images
• View gray value images as a stack of binary images!
Apr 18, 2023 19
Erosion on Gray Value Images
• Images get darker!
Apr 18, 2023 20
Counting Coins
• Counting coins is difficult because they touch each other!
• Solution: Binarization and Erosion separates them!
Apr 18, 2023 21
DILATIONDILATION
04/18/23 22
Example: Dilation• Dilation is an important morphological
operation
• Applied Structuring Element:
Apr 18, 2023 23
Dilation
• Dilation is the set of all points in the image, where the structuring element “touches” the foreground.
• Consider each pixel in the input image– If the structuring element touches the foreground
image, write a “1” at the origin of the structuring element!
• Input:– Binary Image
– Structuring Element, containing only 1s!!
Apr 18, 2023 24
Example for Dilation
Apr 18, 2023 25
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1Output Image
111
Example for Dilation
Apr 18, 2023 26
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0Output Image
111
Example for Dilation
Apr 18, 2023 27
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1Output Image
111
Example for Dilation
Apr 18, 2023 28
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1 1Output Image
111
Example for Dilation
Apr 18, 2023 29
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1 1 1Output Image
111
Example for Dilation
Apr 18, 2023 30
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1 1 1 1Output Image
111
Example for Dilation
Apr 18, 2023 31
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1 1 1 1 1Output Image
111
Example for Dilation
Apr 18, 2023 32
1 0 0 0 1 1 1 0 1 1Input image
Structuring Element
1 0 1 1 1 1 1 1Output Image
111
Another Dilation Example
• Image get lighter, more uniform intensity
Apr 18, 2023 33
Dilation on Gray Value Images
• View gray value images as a stack of binary images!
Apr 18, 2023 34
Dilation on Gray Value Images
• More uniform intensity
Apr 18, 2023 35
Edge Detection
• Edge Detection
1. Dilate input image
2. Subtract input image from dilated image
3. Edges remain!
Apr 18, 2023 36
Opening & Closing
• Important operations
• Derived from the fundamental operations – Dilatation– Erosion
• Usually applied to binary images, but gray value images are also possible
• Opening and closing are dual operations
Apr 18, 2023 37
OPENINGOPENING
04/18/23 38
Opening
• Similar to Erosion– Spot and noise removal– Less destructive
• Erosion next dilation• the same structuring element for both operations.• Input:
– Binary Image– Structuring Element, containing only 1s!
Apr 18, 2023 39
Opening
• Take the structuring element (SE) and slide it around inside each foreground region. – All pixels which can be covered by the SE with the SE
being entirely within the foreground region will be preserved.
– All foreground pixels which can not be reached by the structuring element without lapping over the edge of the foreground object will be eroded away!
• Opening is idempotent: Repeated application has no further effects!
Apr 18, 2023 40
Opening
• Structuring element: 3x3 square
Apr 18, 2023 41
Opening Example
• Opening with a 11 pixel diameter disc
Apr 18, 2023 42
Opening Example
• 3x9 and 9x3 Structuring Element
Apr 18, 2023 43
3*9
9*3
Opening on Gray Value Images
• 5x5 square structuring element
Apr 18, 2023 44
Use Opening for Separating Blobs
• Use large structuring element that fits into the big blobs
• Structuring Element: 11 pixel disc
Apr 18, 2023 45
CLOSINGCLOSING
04/18/23 46
Closing
• Similar to Dilation– Removal of holes– Tends to enlarge regions, shrink background
• Closing is defined as a Dilatation, followed by an Erosion using the same structuring element for both operations.
• Dilation next erosion!• Input:
– Binary Image– Structuring Element, containing only 1s!
Apr 18, 2023 47
Closing
• Take the structuring element (SE) and slide it around outside each foreground region. – All background pixels which can be covered by the SE
with the SE being entirely within the background region will be preserved.
– All background pixels which can not be reached by the structuring element without lapping over the edge of the foreground object will be turned into a foreground.
• Opening is idempotent: Repeated application has no further effects!
Apr 18, 2023 48
Closing
• Structuring element: 3x3 square
Apr 18, 2023 49
Closing Example
• Closing operation with a 22 pixel disc
• Closes small holes in the foreground
Apr 18, 2023 50
Closing Example 1
1. Threshold
2. Closing with disc of size 20
Apr 18, 2023 51 Thresholded closed
Closing Example 2
• Good for further processing: E.g. Skeleton operation looks better for closed image!
52
skeleton of Thresholded
skeleton of Thresholded and next closed
Closing Gray Value Images
• 5x5 square structuring element
Apr 18, 2023 53
Opening & Closing
• Opening is the dual of closing
• i.e. opening the foreground pixels with a particular structuring element
• is equivalent to closing the background pixels with the same element.
Apr 18, 2023 54
HIT and HIT and MISSMISS
04/18/23 55
Hit-and-miss Transform
• Used to look for particular patterns of foreground and background pixels
• Very simple object recognition• All other morphological operations can be
derived from it!!• Input:
– Binary Image– Structuring Element, containing 0s and 1s!!
Apr 18, 2023 56
Hit-and-miss Transform
• Example for a Hit-and-miss Structuring Element• Contains 0s, 1s and don’t care’s.• Usually a “1” at the origin!
Apr 18, 2023 57
Hit-and-miss Transform
• Similar to Pattern Matching:
• If foreground and background pixels in the structuring element exactly match foreground and background pixels in the image, then the pixel underneath the origin of the structuring element is set to the foreground color.
Apr 18, 2023 58
Corner Detection with Hit-and-miss Transform
• Structuring Elements representing four corners
Apr 18, 2023 59
Corner Detection with Hit-and-miss Transform
• Apply each Structuring Element
• Use OR operation to combine the four results
Apr 18, 2023 60
Basic Basic THINNINGTHINNING
04/18/23 61
Thinning
1. Used to remove selected foreground pixels from binary images
2. After edge detection, lines are often thicker than one pixel.
3. Thinning can be used to thin those line to one pixel width.
Apr 18, 2023 62
Definition of Thinning
• Let K be a kernel and I be an image
with 0-1=0!!• If foreground and background fit the structuring
element exactly, then the pixel at the origin of the SE is set to 0
• Note that the value of the SE at the origin is 1 or don’t care!
Apr 18, 2023 63
KIIKI ,HitAndMiss,thin
Example Thinning
Apr 18, 2023 64
We use two Hit-and-miss Transforms
Basic Basic THICKENINGTHICKENING
04/18/23 65
Thickening
• Used to grow selected regions of foreground pixels
• E.g. applications like approximation of convex hull
Apr 18, 2023 66
Definition Thickening
• Let K be a kernel and I be an image
with 1+1=1• If foreground and background match exactly the
SE, then set the pixel at its origin to 1!• Note that the value of the SE at the origin is 0 or
don’t care!
Apr 18, 2023 67
KIIKI ,HitAndMiss,thicken
Example Thickening
Apr 18, 2023 68
PROBLEMSPROBLEMS
04/18/23 69
Problems
1. Consider the images on slide 17! Why are the images getting darker under erosion? Explain!
2. Consider the images on slide 31! Why are the intensities becoming more uniform? Explain!
3. Compare Dilatation and Erosion! How are they related? Verify your answers with Matlab!
4. Apply Erosion and Dilatation for noise removal!
5. Consider slide 38: Remove the artefacts remaining with the horizontal lines.
Apr 18, 2023 70
Problems
6. Derive dilatation and erosion from the Hit-and-miss transformation
Apr 18, 2023 71
Sources Used
Volker Krüger & Rune Andersen
University of Aalborg, Esbjerg
Apr 18, 2023 72