05 Image Acquisition
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Transcript of 05 Image Acquisition
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Pattern Recognition
Kardi Teknomo, PhD
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Kardi Teknomo, PhD
Overview Image & digital image
,
Color, gray and binary image
mage qua y an s orage s ze
Color model eo
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Digital Acquisition Digital acquisition is the process of
(sound, image) into a form suitable for
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Image An image is an electromagnetic radiation that enters
the human visual system through eyes and is incident
upon the cells of the retina.
Wave engt is etween 4, an 7,7 Angstrom(violet and red), i.e. between 4 10^(7) and 7.7
10^
7 m.
Light enters through pupil, the circular opening in the
center ofiris, passes through the crystalline lens, andvitreous humor to be converged to a nodal point and isfocused on the retina
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Human Eyes
Picture source: HumanBody, BritannicaIllustrated ScienceLibrary
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Eye is equivalent to a camera Retina = film
Aperture controls the amount of light that
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Digital Camera Two types of sensor:
Char e Cou led Devices CCD
Complementary Metal OxideSemiconductor (CMOS)
Both are N by M rectangular
grid photosensor (sensitive tolight intensity)
Picture source: Technology, Britannica Illustrated Science Library
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CCD/CMOS
In CMOS, diodes are replaced with CMOS sensor (noisier
Picture source: Technology, Britannica Illustrated Science Library
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Digital image Digital image is a finite
samples (pixels) of anyobservable object
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Pixels The elementary unit of the digital image is the pixel,
which is an abbreviation ofpicture element
1 pixel = 1 cell in the matrix = 1 dot in printer orscreen monitor
A pixel is also the smallest unit of resolution on themonitor or rinter.
Resolution depends on the device (DPI = dots per inch)
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Resolution
Resolution = number of pixels per inch
A digital camera can capture images at differentresolutions, i.e. using a different amount of pixels.
Low resolution: 320 240 or 352 288 ixels ima e
Medium resolution: 640 480 pixels/image.
High resolution: 1216
912 (or 1600
1200) pixels/image
Spatial resolution of an image is the image size inpixels, which corresponds to the size of the CCD (or
Matrix size
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Effect of resolution
The same picture,different resolution
a.
256 x 256b. 128 x 128
.
d. 32 x 32
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Bits
Digital image consists ofN * Mpixels, each represented by kbits.
p xe can us avedifferent values
The pixel values are consideredas integers varying from 0 (black
p xe o - w e p xe .
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Number of gray levels
The same image size256 x 256 pixels,
different in number ofgray levels:
a.
b. 16 (4 bits)
c. 8 (3 bits)d. 4 (2 bits)
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Digitization Parameters
The main parameters of the digitization are:
grid. Pixel accuracy: how many bits are used per sample.
These two arameters have a direct effect onthe image quality but also to the storage size ofthe image
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Effect to Image QualityPixel accuracy
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Effect to storage size
1 byte = 8 bits
E.g: 32 x 32 at 1 bit per pixel = 1024 bits = 128 bytes
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Practice-1 (5 minutes)
You found an image size 256 by 384 pixels.,
exact). What is most probable the pixelaccuracy in bits per pixel?
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Color Image
Typical color acquisition in the digital cameras uses red,green and blue (RGB) filters
At each pixel location, each color component isrepresented by 8 bits (256 different values: 0-255)
Hence the overall amount of different colors that can
be re resented b each ixel are 256^3 =16 777 216colors.
For icon 8 bits er ixel 256 colors
is usually enough
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Gray Level Image
A grayscale image is only one colors are shades of gray.
= =
Simpler because only a single intensity value for each pixel 8-bit integer = 256 possible different shades of gray from
black to white (0-255).
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Binary Image
Each pixel contains 1 bit information
Simplest & fastest to process
mage : rocess nary a e nary
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Practice-2 (5-10 minutes)
Take any color image from Google Image or
Using ImageJ:
Show Info)
Reduce pixel accuracy to 8 bits color image withnumber of colors = 128, 64 and 28 (Image > Type).
Reduce pixel to 32 bits, 16 bits, 8 bits gray scale. .
.
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RGB Primary Colors
Standardization by the CIE (Commission Internationalede l'Eclairage - International Commission onIllumination) in 1931 states the following specificwavelength values to the primary colors:
.
green (G)= 546.1 nm
red (R) = 700.0 nm
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Sensitivity of human eyes
The color sensors in the human eye, which are- -, ,
sensitive are actually cover a range of long,medium, and short wavelengths.
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Mixing the colors of light
RGB Secondary colors:
agen a re + ue
Cyan (green + blue)
Ye ow re + green
Mixed all colors: White (R+G+B)
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RGB Color Model
RGB color model can be described as a triple, , , , ,
normalized into range of [0,1].
r+g+b= 1
rR
= gG
= bB
=
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RGB Color Space: Cube
G
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Practice
Find the corresponding RGB values of the followingRGB color model
(0.1432, 0.2864, 0.5705)
Black (0, 0, 0)
, ,
Yellow (1, 1, 0)
Magenta (1, 0, 1)
Find the RGB color model of the following RGB values
, ,
(255, 128, 64)
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CMY Color model
Used for offset printing
, ,
and Y(yellow).
colors of CMY, and vice versa.
by
C=1-R
M=1-G
Y=1-B
K di T k PhD
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Mixing the color of ink
CMY Secondary colors:
ue agen a + yan
Red (Yellow + Magenta)
reen Ye ow + yan
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Advantages of YUV
The brightness information is separated from the colorinformation
The correlations between the color components arereduced each com onent can be com ressed
separately
component, while the information content in the UandVis less the contrast of the Ycomponent is much
YUV color system is adopted in the JPEG imagecompress on s an ar
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Example of Color Separation
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HSI color model
HSI model consists ofhue(H), saturation(S),.
Intensity corresponds to the luminance (brightness)component (Y) of the YUV models.
Hue is an attribute associated with the dominantwavelength in a mixture of light waves, i.e. the
.
Saturation refers to relative purity of the amount ofwhite light mixed with hue
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Advantages of HSI
The intensity is separated from the color
intimately related to the way in which human
bein s erceive color
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,
HSI Color Space
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Conversion Formula
Intensity ( )I R G B= + +1
3
Hue ( ) ( )[ ]R G R B=
+
11
21
( ) ( )( )
( ) ( )
R G R B G B
R G R B
+
+
360
1 1
2D
( ) ( )( )H
R G R B G B=
+
1
360 2D
cos , otherwise
( )3
S=1- min , ,R G B
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Video
If a sequence of image is projected at more,
cannot realize that they are looking at asequence of discrete images.
Video and movies use this principle to produce
the sensation of moving images.
Video = image sequence
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Digital Video
Digital video is a sequence of frames, each of them is adigital image, whose basic element, as we have seen, isthe pixel
,has to display at least 25 frames per second.
In igita vi eo, t e ratio etween t e orizonta anthe vertical dimension is 4/3, whereas the digital screenusuall has 640480 or 800600 ixels. Hi h-
definition television usually has 1280720 pixels andthe ratio between the horizontal and the vertical
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Averaging Noisy Image
More frames = moreinformation we can use
Averaging noisy imageo one marrow:
a. 1 frame
b. Avera e 4 framesc. Average 16 frames
d. Average 256 frames
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Practice
How much memory is required tostore the movie Titanicin itsuncompressed version?
Assume t at t e movie is co or,has 30 frame/sec (each frame is
640480 ixels its runtime is194 minutes.
For sake of simplicity, do not
store the audio of the movie.
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Assignment
Find the corresponding YUV and HSI values of
(255, 128, 64) (255, 255, 255)
(64, 84, 146)