1. EE4328, Section 005 Introduction to Digital Image Processing Image Segmentation Zhou Wang Dept. of Electrical Engineering The Univ. of Texas at Arlington Fall 2006

2. Concepts and Approaches
What is Image Segmentation?
Image Segmentation Methods
Thresholding
Boundary-based
Region-based: region growing, splitting and merging
Partition an image into regions, each associated with an object
but what defines an object?
From Prof. Xin Li

3. From [Gonzalez & Woods]
Thresholding Method
thresholding
From Prof. Xin Li
histogram
single threshold
multiple thresholds
From [Gonzalez & Woods]

4. From [Gonzalez & Woods]
Thresholding Method
Global Thresholding: When does It Work?
From [Gonzalez & Woods]

5. From [Gonzalez & Woods]
Thresholding Method
Global Thresholding: When does It NOT Work?
A meaningful global threshold may not exist
Image-dependent
global
thresholding
From [Gonzalez & Woods]

6. Thresholding Method true object boundary Thresholding T = 4.5

7. Thresholding Method Solution Spatially adaptive thresholding
Localized processing
Split

8. spatially adaptive threshold selection
Thresholding Method
spatially adaptive threshold selection
Thresholding T = 4
Thresholding T = 7
Thresholding T = 4
Thresholding T = 7

9. merge local segmentation results
Thresholding Method
merge local segmentation results
merge
merge
merge
merge

10. Boundary-Based Method
edge
detection
boundary
detection
classification
and labeling
image
segmentation
From Prof. Xin Li

11. Boundary-Based Method
Advanced Method: Active Contour (Snake) Model
Iteratively update contour (region boundary)
Partial differential equation (PDE) based optimization
From Prof. Xin Li

12. Region-Based Method: Region Growing Key: similarity measure
Start from a seed, and let it grow (include similar neighborhood)
Key: similarity measure
From [Gonzalez & Woods]

13. Region-Based Method: Split and Merge
Iteratively split (non-similar region) and merge (similar regions)
Example: quadtree approach
From [Gonzalez & Woods]

14. Region-Based Method: Split and Merge
Example: Quadtree Split and Merge Procedure
Iteration 1
split
merge
original image
4 regions
4 regions
(nothing to merge)
Split Step  split every non-uniform region to 4
Merge Step  merge all uniform adjacent regions

15. Region-Based Method: Split and Merge
Example: Quadtree Split and Merge Procedure
Iteration 2
split
merge
from Iteration 1
13 regions
4 regions
Split Step  split every non-uniform region to 4
Merge Step  merge all uniform adjacent regions

16. Region-Based Method: Split and Merge
Example: Quadtree Split and Merge Procedure
Iteration 3
split
merge
from Iteration 2
10 regions
2 regions
Split Step  split every non-uniform region to 4
Merge Step  merge all uniform adjacent regions
final segmentation result

17. Hard Problem: Textures Similarity measure makes the difference
From Prof. Xin Li