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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Kardi Teknomo, PhD

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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Kardi Teknomo, PhD

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

Kardi Teknomo, PhD


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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

Kardi Teknomo, PhD


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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)

05 image acquisition

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