Chapter 8 computer vision
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Chapter 8 Computer Vision. Contents. What is Image Processing? Digital Image Processing Electromagnetic Spectrum Steps in Digital Image Processing. What is Image Processing?. Application Area. Image Processing Fields. Image Processing Fields. Digital Image Processing.

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Chapter 8 Computer Vision

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Chapter 8 Computer Vision


Contents

  • What is Image Processing?

  • Digital Image Processing

  • Electromagnetic Spectrum

  • Steps in Digital Image Processing

Chapter 9


What is Image Processing?

Chapter 9


Application Area

Chapter 9


Image Processing Fields

Chapter 9


Image Processing Fields

Chapter 9


Digital Image Processing

  • “Digital Image”?

    • Digital

    • Image

  • “Image Processing”?

Chapter 9


Digital Image Processing

What is a signal?

A signal is a function that maps a set (domain) to another set (range)

Chapter 9


Digital Image Processing

A signal is a function that maps a set (domain) to another set (range)

For each point in time (t), assign a voltage value (y(t)).

Domain = time interval

Range = voltage interval

Chapter 9


Digital Image Processing

  • Image

    • An image is a two-dimensional signal

A signal is called two-dimensional

if the domain is two-dimensional

Chapter 9


Digital Image Processing

  • Image

    • An image is a two-dimensional signal

Chapter 9


Digital Image Processing

  • Digital Image

    • Vs Analog image?

  • Digital vs analog signal

Chapter 9


Signal Types

  • Domain

  • Range

    • Countable

      • Quantized Signal

Chapter 9


Digital Signal

  • A signal is “digital”

    • if both the domain andthe rangeare countable

    • I.e., if it is a quantized discrete-time (or -space) signal

Chapter 9


Digital Image Processing

  • Digital Image

    • A digital image is a two-dimensional signal with a countable domain and a countable range

Chapter 9


Digital Image Processing

  • Digital Image

Chapter 9


Digital Signal

  • How is a digital signal formed?

    • Discrete domain

      • Domain is inherently discrete, or

      • Sample a continuous interval

    • Discrete range

      • Range is inherently discrete, or

      • Sample a continuous interval

Chapter 9


Domain and Range

  • Continuous-time signals

    • t and y (t) have physical meanings

  • Digital signals

    • n and y (n) do not have physical meanings and can be arbitrary

Chapter 9


Digital Image Processing Fields

Chapter 9


Digital Images: 80 years ago

1921

Range has 5 values!

1922

1929

Chapter 9


1 2 3 4 5 6 7

Electromagnetic Spectrum : EM

Chapter 9


1. Gamma-Ray Imaging

Chapter 9


2. X-ray Imaging

Chapter 9


3. UV Imaging

Chapter 9


4. Visible Range

Chapter 9


4. Visible Range

1964

Chapter 9


4. Visible Range

Chapter 9


4. Multispectral: Visible+Infrared Bands

Chapter 9


4. Multispectral: Visible+Infrared Bands

Chapter 9


4. Multispectral: Visible+Infrared Bands

Chapter 9


4. Multispectral: Visible+Infrared Bands

Chapter 9


5. Infrared Range

Chapter 9


6. Microwave Imaging: Radar

Chapter 9


7. Radio Band Imaging

Chapter 9


Electromagnetic Spectrum

Chapter 9


Chapter 9


Ultrasound Image

head

head

Chapter 9


Chapter 9


Chapter 9


4

5

6

7

8

3

11

2

9

1

10

Steps in Digital Image Processing

Chapter 9


1

Chapter 9


2

Chapter 9


Distorted image

Restore image

3

Chapter 9


4

Chapter 9


5

Chapter 9


6

Chapter 9


7

Chapter 9


8

Chapter 9


9

Chapter 9


9

Chapter 9


10

Chapter 9


Knowledge Base

11

Chapter 9


Image Enhancement

in the Spatial Domain


Contents

  • Spatial Domain

  • Point Process

  • Transformation functions

  • Histogram

  • Spatial Filtering

  • Mask Operation

  • Image Enhancement

  • Smoothing Filter

Chapter 9


Spatially Varying Signal

Chapter 9


Spatiotemporal Signals

Chapter 9


Image Processing

  • An image processing system maps an input image to an output image

Output images

Input images

Chapter 9


Image Processing

  • Output pixel depends on the input image pixels

  • Usually:

Chapter 9


Transformation functions

1. contrast stretching

2. point processing : Thresholding Function

Transformation function

s= T [r]

Chapter 9


Transformation functions

Chapter 9


Transformation functions

light

dark

s

s= T [r]

r

Chapter 9

dark light


Transformation functions

original image

negative transformation

s= L-1 -r

Chapter 9


Power-Law Transformations

 = 3

 = 4

 = 5

s= cr

มืดลง

Chapter 9


Contrast Stretching

Chapter 9


Histogram

  • Count the number of pixels with each gray level

Chapter 9


Histogram

Chapter 9


Histogram

Chapter 9


Chapter 9


Histogram Equalization

Chapter 9


Histogram Equalization

Chapter 9


Histogram Equalization

Chapter 9


Spatial Filtering

ค่าน้ำหนัก

ค่าPixels

Chapter 9


Laplacian Output

Chapter 9


Image Enhancement

Chapter 9


Image Enhancement

Chapter 9


Image Segmentation


Line Detection

  • horizontal,... +45 degree,.. vertical... and -45 degree masks

  • Horizontal mask will result with max response when a line passed through the middle row of the mask with a constant background.

  • the similar idea is used with other masks.

  • note: the preferred direction of each mask is weighted with a larger coefficient ....(i.e.,2)than other possible directions.

Chapter 9


Example

Chapter 9


Example

Chapter 9


link criteria:

1). the pixels belonged to one of the set of pixels linked according to the highest count

2). no gaps were longer than 5 pixels

Chapter 9


Result of applying T

Chapter 9


The End

Chapter 9


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