Introduction to Digital Images

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Introduction to Digital Images

• Thomas Moeslund
• Computer Vision and Media Technology lab.
• Aalborg University
• tbm_at_cvmt.dk

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Hvorfor skal ST stud. høre om billeder ?

• Mange billed optagere i sundheds sektoren MR,
  CT, PET,
• Mange billeder i hverdagen

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Agenda

• Hvad er digitale billeder (definitioner)
• Hvordan kan computeren bruges til at behandle
  billeder (billedbehandling)
• Generelt
• Medicinske billeder

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Image definitions
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Where does an image come from?
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Where does an image come from?
Charged coupled device CCD-chip
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Where does an image come from?
Under exposed
Correct exposed

• Integration over time
• Exposure time
• Maximum charge
• Saturation
• Blooming

Over exposed
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Where does an image come from?

• Image elements, picture elements, pels, pixels

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Imaging system

• Image acquisition
• Illumination
• Passive sun
• Active ordinary lamp, X-ray, radar, IR
• Camera lens
• Focus the light on the CCD chip

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Digital Image Representation

• Image is seen as a discrete function f(x,y) as
  opposed to a continuous function (show)
• x and y cannot take on any value!

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Digital Image Representation
Width

• An image f(x,y) is represented
• as an Array
• Width
• number of pixels in x-direction
• Height number of pixels in y-direction
• Size (width x height, width gt height)
• ROI region of interest
• To reduce the amount of data

Height
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Spatial Image Resolution

• Resolution
• The size of an area in a scene that is
  represented
• by one pixel in the image
• Different Resolutions are possible
  (256x256.16x16)
• Lower resolution leads to data reduction!

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Digital Image Representation

• Pixel representation (bits)
• A few words on bits and bytes One bit 0,1
• One byte eight bits
• One pixel one byte eight bits one number
  0,255 (show)
• Grey-scale, intensity, black/white 8 bits
  0,255
• Binary image 1 bit 0,1. Black and white
  visualized as 8 bit 0,255

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Receptivity of the Eye Cells
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RGB Color Space
A single pixel consists of three components
0,255. Each pixel is a Vector.
(0,0)

Pixel-Vector in the computer memory
Final pixel in the image
Caution! Sometimes pixels are not stored as
vectors. Instead, first is stored the complete
red component, then the complete green, then blue.
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Example RGB
R-Component
Original Image
G-Component
B-Component
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Gray-level Resolution Quantization

• Different gray-level resolutions 256, 128, , 2
• Less gray-levels leads to data reduction.
• For 256, 128, 64 gray-levels Difference hardly
  visible

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Applications
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Image manipulation

• Image improvement, e.g. too dark image
• Rotate scale

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Conveyer belt applications

• Checking and sorting
• For example checking bottles in the supermarket
• Quality control
• Does the object have the correct dimensions,
  color, shape, etc.?
• Is the object broken?
• Robot control
• Find precise location of the object to be picked

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Biometrics

• Recognizing/verifying the identity of a person by
  analyzing one or more characteristics of the
  human body
• Characteristics
• Fingerprint, eye (retina, iris), ear, face, heat
  profile, shape (3D face, hand), motion (gait,
  writing),
• Applications
• Verifying Access control (bio-passports)
• Recognizing Surveillance 9/11

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Chroma keying
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Analysis of Sport Motions

• Here Analysis of motion of Sarah Hughes
• 3D Tracking of body parts
• Motion interpretation
• Action recognition

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Motion Capture

• Special effects
• Advertising
• Movies
• Vurdering af gang
• Hvad er der galt?
• Hvor godt er man
• helbredt ?

Andy Serkis
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Motion Capture
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Medical Image Processing

• Image Processing is widely used
• E.g. Automatisk Analysis of microscopic images

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Sædkvalitet
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Sædkvalitet
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Medical Image Processing

• MR/CT Imaging of a human body
• Use for Brain Surgery

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Find blodkar
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Mål hjernebarken
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Mål hjernebarken
Inner surface
Outer surface
Initial surface
MRI Data
Max
Min
Measurements
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Alzheimers Patient Two Time Points
26.09.1997 Thickness 2.03 mm Volume 349670 mm3
6 months
02.04.1998 Thickness 1.84 mm Volume 315561 mm3
Decrease 9
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Medical Image Processing

• Tarm
• (2 videoer)

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The end!
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Opgaver til mm4 i GT-kurset

• Konvertere flg. Base-10 tal til binære tal
• 211 260 -12 7.5
• Vi har målt et signal der svinger mellem
• -3 Volt og 5 Volt. Vi vil lave en A/D-converter
  med en opløsning på 0.1
• Hvor mange bits skal vi bruge ?
• Lave en algoritme der kan konvertere fra base 10
  til base 2
• NB Den skal kun kunne konvertere heltal i
  intervallet 0,200
• I HTML kode skrives en 100 Grøn farve sådan
  00FF00
• Hvorfor ?

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Why are digital images interesting?

• Humans are visual creatures in a
• visual world
• Images are (often) the primary sense
• Imagine you could only keep one sense
• A picture is worth a 1000 words
• Words are many times ambiguous
• So, if we want to build systems capable of human
  skills, then they should be capable of
  understanding images (many applications)
• Hvorfor skal ST stud. høre om billeder ?
• Mange billede optagere I sundheds sektoren MR,
  CT, PET,
• Mange billeder i hverdagen

38
Image file types

• image.jpg, image.tif, image.gif, image.png,
  image.ppm, .
• Raw
• No data is lost
• Header data (234 235 32 21)
• For example image.pgm
• The file can be viewed
• Lossless compression
• No data is lost, but the file cannot be viewed
• For example image.gif
• Lossy compression
• Better compression
• Some data is lost (optimized from the HVS point
  of view)
• The file cannot be viewed
• For example image.jpg