image segmentation (chapter 10)

21
Image Segmentation (Chapter 10) CSC 446 Lecturer: Nada ALZaben

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Image Segmentation (Chapter 10). CSC 446 Lecturer: Nada ALZaben. Introduction. Segmentation subdivides an image into its constituent regions or objects. The level of subdivision is done depending on the level where we isolate the object of interest in the application from the background. - PowerPoint PPT Presentation

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Page 1: Image Segmentation (Chapter 10)

Image Segmentation(Chapter 10)

CSC 446 Lecturer: Nada ALZaben

Page 2: Image Segmentation (Chapter 10)

IntroductionSegmentation subdivides an image

into its constituent regions or objects.

The level of subdivision is done depending on the level where we isolate the object of interest in the application from the background.

Segmentation is a preprocessing algorithm for feature extraction.

Page 3: Image Segmentation (Chapter 10)

Segmentation Techniques 1) Detection of discontinuities

1) Point detection 2) Line detection 3) Edge detection

2) Detection of similarities.

Page 4: Image Segmentation (Chapter 10)

Detection of discontinuities Will apply the mask 3X3 on image

and get R: R=w1z1+w2z2+……+w9z9

1. Point detection: we detect isolated points where

W1 W2 W3

W4 W5 W6

W7 W8 w9

-1 -1 -1

-1 8 -1

-1 -1 -1

Page 5: Image Segmentation (Chapter 10)

Detection of discontinuities

2. Line detection: we detect lines by computing R1,R2,R3 and R4 using the 4 masks

Page 6: Image Segmentation (Chapter 10)

Detection of discontinuities

3. Edge detection: it contains horizontal and vertical edge estimates

and

Page 7: Image Segmentation (Chapter 10)

Gx Gy

Gy

Gy

Gx

Gx

Page 8: Image Segmentation (Chapter 10)
Page 9: Image Segmentation (Chapter 10)
Page 10: Image Segmentation (Chapter 10)

Example :0 0 0 0 0

0 0 0 0 0

0 0 3 3 3

0 0 3 3 3

0 0 3 3 3

0 0 3 3 3

-1 1

-1 1

-1 -1

1 1

0 0 0 0 0

0 0 0 0 0

0 0 3 0 0

0 0 6 0 0

0 0 6 0 0

0 0 6 0 0

0 0 0 0 0

0 0 0 0 0

0 0 3 6 6

0 0 0 0 0

0 0 0 0 0

0 0 0 0 0

Page 11: Image Segmentation (Chapter 10)

Representation and Description (Chapter 11)

CSC 446 Lecturer: Nada ALZaben

Page 12: Image Segmentation (Chapter 10)

Introduction The data resulted from

segmentation need to be represented and described in a way that can be processed in another step.

Representing a region can be in 2 ways:

1. In term of its boundary's.2. In term of its internal

characteristics. After representing the data it

needs to be described either by its length, area,….etc.

Page 13: Image Segmentation (Chapter 10)

Representation (Chain Code)

Chain code are used to represent a boundary by a connected square of straight line segments of specific length and direction.

It is based on 4 or 8 connectivity of the segments.

The direction of each segment is coded using number schema.

Page 14: Image Segmentation (Chapter 10)

Chain Code

Page 15: Image Segmentation (Chapter 10)

Chain CodeDisadvantages:1. The result chain code is long2. If the boundary has some

disturbance cause changes in the chain code

Solution use grid.

Page 16: Image Segmentation (Chapter 10)

Chain Code Example

Page 17: Image Segmentation (Chapter 10)

Chain Code Example 1

Input: 446567001232

Page 18: Image Segmentation (Chapter 10)

Chain Code Example 2

Page 19: Image Segmentation (Chapter 10)

Object Recognition (Chapter 12)

CSC 446 Lecturer: Nada ALZaben

Page 20: Image Segmentation (Chapter 10)

Pattern Recognition System

A pattern recognition system is composed of

1. Pre-processing 2. Feature extraction (very important)3. Classification

Scanning and data capture

Preprocessing

segmentation

Feature extraction

Classification

Input image

Classes

Page 21: Image Segmentation (Chapter 10)

GOOD LUCK