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Chapter 9: Morphological Image Processing Digital Image Processing

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Page 1: Chapter 9: Morphological Image Processing Digital Image Processing

Chapter 9: Morphological Image Processing

Digital Image Processing

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Mathematic Morphology used to extract image components that are

useful in the representation and description of region shape, such as boundaries extraction skeletons convex hull morphological filtering thinning pruning

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Mathematic Morphology

mathematical framework used for: pre-processing

noise filtering, shape simplification, ... enhancing object structure

skeletonization, convex hull... Segmentation

watershed,… quantitative description

area, perimeter, ...

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Z2 and Z3

set in mathematic morphology represent objects in an image binary image (0 = white, 1 = black) : the

element of the set is the coordinates (x,y) of pixel belong to the object Z2

gray-scaled image : the element of the set is the coordinates (x,y) of pixel belong to the object and the gray levels Z3

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Basic Set Theory

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Reflection and Translation

} ,|{ˆ Bfor bbwwB

} ,|{)( Afor azaccA z

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Logic Operations

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Example

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Structuring element (SE)

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small set to probe the image under study for each SE, define origo shape and size must be adapted to geometricproperties for the objects

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Basic idea in parallel for each pixel in binary

image: check if SE is ”satisfied” output pixel is set to 0 or 1 depending on

used operation

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How to describe SE many different ways! information needed:

position of origo for SE positions of elements belonging to SE

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Basic morphological operations

Erosion

Dilation

combine to Opening object Closening background

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keep general shape but smooth with respect to

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Erosion Does the structuring element fit the

set?erosion of a set A by structuring

element B: all z in A such that B is in A when origin of B=z

shrink the object

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}{ Az|(B)BA z

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Erosion

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Erosion

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Erosion

}{ Az|(B)BA z

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Dilation Does the structuring element hit the

set? dilation of a set A by structuring

element B: all z in A such that B hits A when origin of B=z

grow the object17

}ˆ{ ΦA)Bz|(BA z

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Dilation

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Dilation

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Dilation

}ˆ{ ΦA)Bz|(BA z

B = structuring element

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Dilation : Bridging gaps

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useful erosion

removal of structures of certain shape and size, given by SE

Dilation filling of holes of certain shape and size,

given by SE

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Combining erosion and dilation

WANTED: remove structures / fill holes without affecting remaining parts

SOLUTION: combine erosion and dilation (using same SE)

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Erosion : eliminating irrelevant detail

structuring element B = 13x13 pixels of gray level 1

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Opening

erosion followed by dilation, denoted ∘

eliminates protrusions breaks necks smoothes contour

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BBABA )(

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Opening

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Opening

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Opening

BBABA )(})(|){( ABBBA zz

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Closing

dilation followed by erosion, denoted •

smooth contour fuse narrow breaks and long thin gulfs eliminate small holes fill gaps in the contour

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BBABA )(

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Closing

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Closing

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Closing

BBABA )(

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Properties

Opening(i) AB is a subset (subimage) of A(ii) If C is a subset of D, then C B is a subset of D B(iii) (A B) B = A B

Closing(i) A is a subset (subimage) of AB(ii) If C is a subset of D, then C B is a subset of D B(iii) (A B) B = A B

Note: repeated openings/closings has no effect!

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Duality

Opening and closing are dual with respect to complementation and reflection

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)ˆ()( BABA cc

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Useful: open & close

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Application: filtering

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Hit-or-Miss Transformation ⊛ (HMT)

find location of one shape among a set of shapes ”template matching

composite SE: object part (B1) and background part (B2)

does B1 fits the object while, simultaneously, B2 misses the object, i.e., fits the background?

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Hit-or-Miss Transformation

)]([)( XWAXABA c

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Boundary Extraction

)()( BAAA

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Example

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Region Filling,...3,2,1 )( 1 kABXX c

kk

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Example

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Extraction of connected components

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Example

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Convex hull A set A is is

said to be convex if the straight line segment joining any two points in A lies entirely within A.

i

iDAC

4

1)(

,...3,2,1 and 4,3,2,1 )( kiABXX iik

ik

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Thinning

cBAA

BAABA

)(

)(

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Thickening

)( BAABA

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SkeletonsK

kk ASAS

0

)()(

BkBAkBAASk )()()(

})(|max{ kBAkK

))((0

kBASA k

K

k

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Pruning

}{1 BAX

AHXX )( 23

314 XXX

H = 3x3 structuring element of 1’s

)( 1

8

12

k

kBXX

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5 basic structuring elements