what is image segmentation? image segmentation methods thresholding boundary-based
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EE4328, Section 005 Introduction to Digital Image Processing Image Segmentation Zhou Wang Dept. of Electrical Engineering The Univ. of Texas at Arlington Fall 2006. Concepts and Approaches. What is Image Segmentation? Image Segmentation Methods Thresholding Boundary-based - PowerPoint PPT PresentationTRANSCRIPT
EE4328, Section 005 Introduction to Digital Image
Processing
Image Segmentation
Zhou Wang
Dept. of Electrical EngineeringThe Univ. of Texas at Arlington
Fall 2006
• What is Image Segmentation?
• Image Segmentation Methods– Thresholding– Boundary-based– Region-based: region growing, splitting and merging
Concepts and Approaches
Partition an image into regions, each associated with an object but what defines an
object?
From Prof. Xin
Li
Thresholding Method
0 50 100 150 200 2500
0.5
1
1.5
2
2.5
3x 10
4
thresholding
histogram From Prof. Xin Li
single threshold
multiple thresholds
From [Gonzalez & Woods]
Thresholding Method
From [Gonzalez & Woods]
• Global Thresholding: When does It Work?
Thresholding Method
• Global Thresholding: When does It NOT Work?– A meaningful global threshold may not exist– Image-dependent
globalthresholding
From [Gonzalez & Woods]
Thresholding Method
4
4
4
4
5
5
4
4
4
10
5
5
10 11 5
3
3
9
9
9
1 1 2 2 3
1 1 2 2 8
1 1 2 7 8
1 1 6 7 8
1 5 6 7 8
10
11
11
10
5
5
4 11 5
10 11 5
9
3
3
91 5 6 7 8
1 5 6 7 3
1 5 6 2 3
1 5 2 2 3
5
5
5
5
5
5
5
5
5
4 4 531 1 2 2 3 5
0
0
0
0
1
1
0
0
0
1
1
1
1 1 1
0
0
1
1
1
0 0 0 0 0
0 0 0 0 1
0 0 0 1 1
0 0 1 1 1
0 1 1 1 1
1
1
1
1
1
1
0 1 1
1 1 1
1
0
0
10 1 1 1 1
0 1 1 1 0
0 1 1 0 0
0 1 0 0 0
1
1
1
1
1
1
1
1
1
0 0 100 0 0 0 0 1
0
0
0
0
0
0
0
0
0
1
0
0
1 1 0
0
0
1
1
1
0 0 0 0 0
0 0 0 0 1
0 0 0 1 1
0 0 1 1 1
0 0 1 1 1
1
1
1
1
0
0
0 1 0
1 1 0
1
0
0
10 0 1 1 1
0 0 1 1 0
0 0 1 0 0
0 0 0 0 0
0
0
0
0
0
0
0
0
0
0 0 000 0 0 0 0 0
Thresholding T = 4.5
Thresholding T = 5.5
true object boundary
Thresholding Method
1 1 2 2 3
1 1 2 2 8
1 1 2 7 8
1 1 6 7 8
1 5 6 7 8
4
4
4
4
5
5
4
4
4
10
5
5
10 11 5
3
3
9
9
9
5
5
5
5
5
1 5 6 7 8
1 5 6 7 3
1 5 6 2 3
1 5 2 2 3
1 1 2 2 3
10
11
11
10
5
5
4 11 5
10 11 5
9
3
3
9
5
5
5
5
4 4 53 5
4
4
4
4
5
5
4
4
4
10
5
5
10 11 5
3
3
9
9
9
1 1 2 2 3
1 1 2 2 8
1 1 2 7 8
1 1 6 7 8
1 5 6 7 8
10
11
11
10
5
5
4 11 5
10 11 5
9
3
3
91 5 6 7 8
1 5 6 7 3
1 5 6 2 3
1 5 2 2 3
5
5
5
5
5
5
5
5
5
4 4 531 1 2 2 3 5
Split
• Solution– Spatially adaptive thresholding– Localized processing
Thresholding Method
1 1 2 2 3
1 1 2 2 8
1 1 2 7 8
1 1 6 7 8
1 5 6 7 8
4
4
4
4
5
5
4
4
4
10
5
5
10 11 5
3
3
9
9
9
5
5
5
5
5
1 5 6 7 8
1 5 6 7 3
1 5 6 2 3
1 5 2 2 3
1 1 2 2 3
10
11
11
10
5
5
4 11 5
10 11 5
9
3
3
9
5
5
5
5
4 4 53 5
0 0 0 0 0
0 0 0 0 1
0 0 0 1 1
0 0 1 1 1
0 1 1 1 1
0
0
0
0
0
0
0
0
0
1
0
0
1 1 0
0
0
1
1
1
0
0
0
0
0
0 1 1 1 1
0 1 1 1 0
0 1 1 0 0
0 1 0 0 0
0 0 0 0 0
1
1
1
1
0
0
0 1 0
1 1 0
1
0
0
1
0
0
0
0
0 0 00 0
Thresholding T = 4
Thresholding T = 7
Thresholding T = 4
Thresholding T = 7
spatially adaptive threshold selection
Thresholding Method
0
0
0
0
0
0
0
0
0
1
0
0
1 1 0
0
0
1
1
1
0 0 0 0 0
0 0 0 0 1
0 0 0 1 1
0 0 1 1 1
0 1 1 1 1
1
1
1
1
0
0
0 1 0
1 1 0
1
0
0
10 1 1 1 1
0 1 1 1 0
0 1 1 0 0
0 1 0 0 0
0
0
0
0
0
0
0
0
0
0 0 000 0 0 0 0 0
0 0 0 0 0
0 0 0 0 1
0 0 0 1 1
0 0 1 1 1
0 1 1 1 1
0
0
0
0
0
0
0
0
0
1
0
0
1 1 0
0
0
1
1
1
0
0
0
0
0
merge merge
merge merge
merge local segmentation results
0 1 1 1 1
0 1 1 1 0
0 1 1 0 0
0 1 0 0 0
0 0 0 0 0
1
1
1
1
0
0
0 1 0
1 1 0
1
0
0
1
0
0
0
0
0 0 00 0
edgedetection
boundary detection
classificationand labeling
image segmentation
From Prof. Xin Li
Boundary-Based Method
Boundary-Based Method
From Prof. Xin Li
• Advanced Method: Active Contour (Snake) Model– Iteratively update contour (region boundary)– Partial differential equation (PDE) based optimization
Region-Based Method: Region Growing
From [Gonzalez & Woods]
Key: similarit
y measur
e
• Region Growing– Start from a seed, and let it grow (include similar neighborhood)
Region-Based Method: Split and Merge
• Split and Merge– Iteratively split (non-similar region) and merge (similar regions)– Example: quadtree approach
From [Gonzalez & Woods]
Region-Based Method: Split and Merge
original image 4 regions 4 regions(nothing to
merge)
split merge
• Example: Quadtree Split and Merge Procedure
Iteration 1
Split Step split every non-uniform region to 4Merge Step merge all uniform adjacent regions
Region-Based Method: Split and Merge
from Iteration 1 13 regions 4 regions
split merge
• Example: Quadtree Split and Merge Procedure
Iteration 2
Split Step split every non-uniform region to 4Merge Step merge all uniform adjacent regions
Region-Based Method: Split and Merge
from Iteration 2 10 regions
split merge
• Example: Quadtree Split and Merge Procedure
Iteration 3
final segmentation
result
2 regions
Split Step split every non-uniform region to 4Merge Step merge all uniform adjacent regions
Hard Problem: Textures
Similarity measure makes the difference
From Prof. Xin Li