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2011-08-30 E0005E Industrial Image Analysis 1
INSTITUTIONEN FÖR SYSTEMTEKNIK
LULEÅ TEKNISKA UNIVERSITET
2011-08-30 E0005E, Course Introduction 2
E0005E Industrial Image Analysis
Matthew Thurley, Teacher
Anders Landstöm, Lab Assistant
matthew.thurley@ltu.se
anders.p.landstrom@ltu.se
What you need to know
• Course Study guide (read this carefully)
- Course structure, topics, assessment criteria
- This course has a problem based learning approach
- The assignments are Development Phases in the production of an industrial measurement system
• Course web page http://www.ltu.se/edu/course/E00/E0005E/E0005E-Industriell-bildanalys-1.36192?l=en
• Fronter https://fronter.com/ltu/
- Has a virtual room with general course information.
- Submit assignments in Fronter
- login and go to the course room E0005E Industrial Image Analysis H1* There is a Submissions link in the left column.
- Submit in the correct folder. If you are late you will have to submit in the Late Submissions folder
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What you need to know
• Attendance – Make sure you are registered
• Plagarism - ”copying another persons work and presenting it as your own”
- Watch this video
- http://www.youtube.com/watch?v=Mwbw9KF-ACY&feature=related
- Press the CC button to turn english subtitles on or off
- Ephorus compares your submission against millions of documents from the internet and against past submissions in this course
2011-08-30 E0005E, Lecture 3 4
Ephorus Example 4% Match
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2011-08-30 E0005E, Course Introduction 6
Labs
• Labs must be done individually (you can of course discuss problems and solutions with your friends but you must do your own coding and report writing)
• Lab 8 may have some group work, but you still must write your own report
• Helpful documents
- MATLAB-Tips.pdf
- ReportTemplate.doc
2011-08-30 E0005E, Course Introduction 7
The lab environment
• A2506 in the A-building
• We will use Matlab for the assignments
Variable and
directory
browser
Command
history
Command window
DIGITAL IMAGES
Matthew Thurley
E0005E Industrial Image Analysis
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2011-08-30 E0005E Industrial Image Analysis 9
Light
Imaging based on Gamma Rays • Nuclear medicine,
Injecting radioactive isotopes into the body that emit gamma rays (a) or cause the emission of gamma rays (b)
• (c) Gamma ray band image of the ”Cynus Loop” interstellar gas cloud, the remnant of an exploded star
• (d) Gamma ray image of a valve in a nuclear reactor
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Imaging based on Gamma Rays
“An image taken by a gamma ray camera showing the bottom of a ventilation stack standing between Fukushima Daiichi nuclear power plant's No.1 and No.2 reactors, where radiation exceeding 10 sieverts per hour - seen here in red” 2011-08-02 blog post
“a level that could lead to incapacitation or death after just several seconds of exposure”
http://photoblog.msnbc.msn.com/_news/2011/08/02/7227954-lethal-levels-of-radiation-recorded-in-fukushima-gamma-ray-image
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X-ray Imaging • Medicine, familiar chest x-ray (a). An x-
ray source behind the patient sends x-rays through the patient towards a detector on the other side. X-rays are absorbed by tissue and bone reducing the x-ray strength arriving at the detector creating different intensities in the image
• (b) An xray contrast medium has been injected into the aorta of the patient to highlight parts of interest
• (c) X-ray CAT scan (computerized axial tomography)
• (d) Industrial X-ray imaging for defect detection
• (e) Cynus Loop dust cloud
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Ultraviolet Imaging • Flourescence microscopy is a field of
miscroscope imaging where ultraviolet light is used to excite the electrons in a material causing them to flouresce (emit light). Some material flouresce naturally and flourescent chemicals can be applied to a sample
• (a) Miscroscope image of a healthy corn sample treated with flourescent chemicals
• (b) Corn infected by ”smut” disease
• (c) Cynus Loop dust cloud in the high energy ultraviolet band
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• Remote sensing
Visible & Infrared Imaging
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• Industrial Imaging
• Automated visual inspection of manufactured goods
Visible & Infrared Imaging
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• Most common application is radar
• Some radar waves can penetrate clouds and even see through ice (martian polar ice), vegetation or dry sand (sahara desert).
• Imaging radar is an active illumination technique (like a camera with a flash)
• Spaceborne radar can see through clouds and take hi resolution images of the land.
• Consider NASAs detailed radar imaging of Venus which is permanently shrounded in sulfuric acid clouds
Imaging in the Microwave Band
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Image courtesy of JPL
• Magnetic resonance imaging - Pulsed radio waves pass through the patient, radio pulses emminate from the patients body. Complex algorithms determine the source location and strength of these emminations reconstructing a picture of the patients body part.
• Crab Pulsar – naturally emitting source of radio waves
Imaging in the Radio Band
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• Sound
• Ultrasound (medical imaging)
• Siesmic imaging (oil and gas exploration)
• Electron miscroscopy
Imaging from other sources
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Visible Light
• Visible Light is the part of the electromagnetic spectrum that causes a reaction in our visual systems
• Generally these are wavelengths in the range of about 350-750 nm (nanometers)
• Long wavelengths appear as reds and short wavelengths as blues
Three-Color Theory
Human visual system has two types of sensors
• Rods: grayscale, highly sensitive to intensity, superior at night & peripheral vision
• Cones
- Color sensitive
- Three types of cone
- Only three values (the tristimulus values) are sent to the brain
Need only match these three values
• Need only three primary colors
Speaking Notes
• Initial processing of light in most optical systems is based on the human visual system, however, the human visual system has a back end far more complex than any camera.
• The optic nerves are connected to the rods and cones in an extremely complex arrangement with many of the characteristics of a sophisticated signal processor.
• The sensors in the eye do not react uniformly to light energy of different wavelengths (colors)
• Define intensity as the physical measure of light energy
• Define brightness as the measure of how intense we percieve the light to be.
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Color Perception http://en.wikipedia.org/wiki/Color_perception
• Cone cells in the human eye.
• We are most sensitive to green light where all the ranges overlap
• However, red light stimulates almost exclusively L-cones, and blue light almost exclusively S-cones.
Cone
Type
Range
(nm)
Peak
Wavelength
S (blue) 400..500 420-440 nm
M (green) 450..630 534-545 nm
L (red) 500..700 564-580 nm
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Image: WikiCommons
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Digital recording medium
• CCD Charged-Coupled Device
• Bayer mask
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Color and monochromatic representation
• Chromatic light (color)
• Monochromatic light
Prism White light
Intensity of red light
Intensity of green light
Intensity of blue light
White light Intensity of white
light (or grey level)
What is a photographic digital image
• Grid of elements (pixels)
• Each element has a color
• Each color is represented by a number
What is a photographic digital image
• Grid of elements (pixels)
• The image (grid) has a number of rows, and a number of columns
• We identify each pixel by specifying its position (i,j) in the image using a row number i, and a column number j
column j
row i
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Digital image acquisition process
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Image sampling and quantization
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Image sampling and quantization
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Spatial Resolution (Sampling)
• Spatial resolution is a measure of the smallest perceptible detail in an image
- Dots per unit distance
- Dots per inch (DPI)
• 20-megapixel camera can be expected to have better imaging capabilities than a 8-megapixel camera.
• But, size of image does not tell complete story.
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Spatial Resolution
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Intensity Resolution (Quantization)
• Intensity resolution is a measure of the smallest perceptible change in intensity level in an image
- Integer power of two
- 8 bits often used (256 gray levels)
• ‘Smallest perceptible change’
- Not how the human percieve
- Statement on how the intensity is quantized.
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Image sampling and Quantization
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Intensity Resolution (Quantization)
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A few operations
• We will go through
- Point operations
- Histogram calculation
- Contrast stretching
- Thresholdning
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Point operations
• A point operation is an operation where the gray level gi at a certain pixel (i,j) is replaced with a new gray level go according to some mapping go = F(gi)
(i,j)
gi = I(i,j)
go = F(gi)
I(i,j) = go
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Point operations
• Point operations is implemented as a Look Up Table
- If the mapping F(g) is independent of pixel position
2 9 0 1
0 7 4 3
9 8 1 6
3 0 6 2
Original image New image
Look Up Table
0 2 4 8 16 16 16 16 32 64
0 1 2 3 4 5 6 7 8 9
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Histogram calculation
• The histogram of a digital image with intensity levels in the range [0,L-1] is a discrete function
h(rk) = nk
rk - is the kth intensity value
nk - is the number of pixels in the image with intensity rk
• Commonly normalized
p(rk) = nk / NM
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Histogram calculation
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Histogram calculation
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Contrast stretching
• Piecewise-Linear Transformation
- Can design complex transformation functions
• The shape of the transformation
- Controlled by (r1,s1) and (r2,s2)
• Typical transformation for
contrast stretching
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Contrast stretching, an example
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Contrast stretching, an example
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Thresholding
• Creates a binary image
• Useful for identifying objects in images - Calculate size, shape etc.
• Study the histogram to find appropriate threshold values
Reading
• Digital Image Processing (Third Edition) Gonzalez and Woods
- Ch 1
- Ch2 2.1-2.5
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Summing Up
• Consider the following three questions;
- What do I need to work on?
- What have I learnt today?
- What was the main point left unanswered today?
• Write your answers in the provided journal. Write the lecture number 1 on top of the page. Write your name and student number on the back of the book
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