EE4328, Section 005
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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

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What is Image Segmentation? Image Segmentation Methods Thresholding Boundary-based

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EE4328, Section 005 Introduction to Digital Image ProcessingImage SegmentationZhou WangDept. of Electrical EngineeringThe Univ. of Texas at ArlingtonFall 2006


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


Thresholding Method

thresholding

From Prof. Xin Li

histogram

multiple thresholds

single threshold

From [Gonzalez & Woods]


Thresholding Method

  • Global Thresholding: When does It Work?

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]


Thresholding Method

true object boundary

Thresholding T = 4.5

Thresholding T = 5.5


Thresholding Method

  • Solution

    • Spatially adaptive thresholding

    • Localized processing

Split


Thresholding Method

spatially adaptive threshold selection

Thresholding T = 4

Thresholding T = 7

Thresholding T = 4

Thresholding T = 7


Thresholding Method

merge local segmentation results

merge

merge

merge

merge


Boundary-Based Method

boundary

detection

classification

and labeling

edge

detection

image

segmentation

From Prof. Xin Li


Boundary-Based Method

  • Advanced Method: Active Contour (Snake) Model

    • Iteratively update contour (region boundary)

    • Partial differential equation (PDE) based optimization

From Prof. Xin Li


Region-Based Method: Region Growing

  • Region Growing

    • Start from a seed, and let it grow (include similar neighborhood)

Key: similarity measure

From [Gonzalez & Woods]


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

  • Example: Quadtree Split and Merge Procedure

Iteration 1

split

merge

4 regions

4 regions

(nothing to merge)

original image

Split Step split every non-uniform region to 4

MergeStep merge all uniform adjacent regions


Region-Based Method: Split and Merge

  • Example: Quadtree Split and Merge Procedure

Iteration 2

split

merge

13 regions

4 regions

from Iteration 1

Split Step split every non-uniform region to 4

MergeStep merge all uniform adjacent regions


Region-Based Method: Split and Merge

  • Example: Quadtree Split and Merge Procedure

Iteration 3

split

merge

10 regions

2 regions

from Iteration 2

Split Step split every non-uniform region to 4

MergeStep merge all uniform adjacent regions

final segmentation result


Hard Problem: Textures

Similarity measure makes the difference

From Prof. Xin Li


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