POTENTIAL OF MULTISPECTRAL TECHNIQUES FOR …...Potential of multispectral techniques for measuring...

Potential of multispectral techniques for measuring color in the automotive sector (1st BYK-Gardner Iberian Automotive Meeting, 2011)

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POTENTIAL OF MULTISPECTRAL TECHNIQUES FOR MEASURING COLOR IN THE AUTOMOTIVE

SECTOR

Meritxell Vilaseca, Francisco J. Burgos,

Jaume Pujol


Technological innovation center established in

1997 with the aim of structuring the activities in the

field of Optical Engineering (Terrassa Campus of

the Technical University of Catalonia).

http://www.cd6.upc.edu/

http://www.cd6.upc.edu/


Barcelona Vilanova i la Geltrú Castelldefels

Sant Cugat del Vallès

Terrassa

Manresa


4

Visual optics and color group:

J. Pujol M. Vilaseca M. Arjona F. Díaz-Doutón S. Luque F. J. Burgos

M. Aldaba J. A. Herrera H. Zuluaga F. Sanabria J. C. Ondategui E. Ferrer A. Giner

Potential of multispectral and hyperspectral techniques for measuring color in the automotive sector (1st BYK-Gardner Iberian Automotive Meeting, 2011)

Outline

• Introduction

• What is a multispectral system?

• Components of multispectral systems

• Spectral sampling technique

• Calibrating a multispectral system

• Multispectral systems at the CD6

• Applications in the automotive sector

• Hyperspectral systems

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6

Standard instruments for color measurement:

spectroradiometers, spectrophotometers, colorimeters

Introduction

How color is measured?

• Cost (Diffraction grating)

• Integration of the viewing field

• Only one measurement simultaneously

• Slow speed


Introduction

7

High spatial resolution

Linearity

Rapid response

Acceptable SNR

High cuantum efficiency

Wide spectral range

Reduced size

Scientific image

Measurement instrument

with high spatial resolution

2. Color characterization

Instrument for color measurement

Is it possible to perform color measurements

using a digital camera?

1. Control and correction of the noise sources


Introduction

8



RGB

RGB

RGB OUTPUT

CIE-XYZ

CIE-Lab


Introduction

9

colorimetric applications are seriously limited

Commercial digital color camera

CIE Color Matching Functions

Linear

Transformation

(Luther Condition)

Wavelength (nm)

400 450 500 550 600 650 700

xyz -

CIE

1931

0.0

0.5

1.0

1.5

2.0x - CIE 1931

y - CIE 1931

z - CIE 1931

Wavelength (nm)

400 450 500 550 600 650 700

xyz -

Q10 C

CD

co

lou

r cam

era

0.0

0.2

0.4

0.6

0.8

1.0x - Q10 CCD Colour Camera

y - Q10 CCD Colour Camera

z - Q10 CCD Colour Camera

Color Matching Functions of the

digital camera



CIE-XYZ RGB


Introduction

10

The solution:

Multispectral Imaging

Systems




What is a multispectral system?

An imaging system with more than 3 acquisition

channels

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A multispectral system is able to provide spectral information

instantaneously at each pixel of the captured image and therefore it

allows performing more accurate colour measurements.

Wavelength (nm)

400 450 500 550 600 650 700

Re

lati

ve

Sp

ectr

al

Se

ns

itiv

ity

Q1

0 C

CD

co

lou

r c

am

era

0.0

0.2

0.4

0.6

0.8

1.0

Wavelength (nm)

400 450 500 550 600 650 700 750

Tra

nsm

itta

nce

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

F400

F450

F500

F550

F600

F650

F700


12

CIE-1931 XYZ

Color Imaging

Multispectral Imaging


channels



13


channels


Complete spectral information on each pixel of the image

Color Image

R,G,B

Multispectral

Image

Wavelength (nm)

400 440 480 520 560 600 640 680 720 760

Spectr

al re

flecta

nce

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16


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Classification:

They are classified depending on the number of spectral

bands/acquisition channels:

Number of channels Name

1 Monochromatic

3 RGB o trichromatic

4 to 9 Multispectral

10 to 100 Hyperspectral

More than 100 Ultraspectral



Components of multispectral systems

15


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Spectral sampling technique

1. Using a “white” light source and filters:

2. Multiplexed illumination:

+

Building acquisition channels with different

spectral features


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Narrowband filters: interference filters in a filter wheel

Configurations based on monochrome cameras

QImaging

QICAM Fast1394

12-bit cooled

Nikon AF

Nikkor

28-105mm

Motorized

Filter Wheel

QImaging

QICAM Fast1394

12-bit cooled

Nikon AF

Nikkor

28-105mm

Motorized

Filter Wheel

Wavelength (nm)

400 450 500 550 600 650 700 750

Tra

nsm

itta

nce

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

F400

F450

F500

F550

F600

F650

F700

Components of multispectral systems


Spectral sampling techniques

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Narrowband filters: tunable filter (LCTF or AOTF)



Spectral sampling techniques

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2. Multiplexed illumination:


and light-emmiting diodes (LEDs)

http://www.cs.columbia.edu/CAVE/projects/multispectral_imaging/images/capturing_system.gif

http://www.cs.columbia.edu/CAVE/projects/multispectral_imaging/images/capturing_system.gif


Calibrating a multispectral system

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High resolution

Linearity

Rapid response

Acceptable SNR

High cuantum efficiency

Wide spectral range

Reduced size

Scientific image

Measurement instrument

with high spatial resolution

2. Spectral reconstruction and color

measurement algorithm

Instrument for color and spectral measurements

1. Control and correction of the noise sources



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1. Correction of the noise sources:

Temporal noise sources: Image averaging. Determining

the number of images to be averaged. Image averaging

removes all noise sources except the spatial noise sources.

# averaged images

0 10 20 30 40 50 60 70 80

Rela

tive S

NU

P

0.800

0.850

0.900

0.950

1.000

R Channel

G Channel

B Channel



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1. Correction of the noise sources:

Spatial noise sources: Spatial non-uniformity correction,

flat-field correction or „flat-fielding‟.

560

580

600

620

640

660

01020304050607080

010

2030405060

Dig

ita

l V

alu

e

Colu

mns

Rows

560

580

600

620

640

660

560

580

600

620

640

660

01020304050607080

010

2030405060

Dig

ita

l Le

ve

l

Colu

mn

Row

560

580

600

620

640

660



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2. Spectral reconstruction and color measurement

How can we obtain spectral properties (reflectance,

radiance…) from multispectral images?

Wavelength (nm)

400 500 600 700

Re

fle

cta

nce

0.2

0.4

0.6

0.8

1.0

1.2

ND r(l)


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Use of training sets:

2. Spectral reconstruction and color measurement


ND r(l)


Multispectral systems at the CD6

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Multispectral system in the near-infrared (800 –

1000 nm)

800 1000 nm 380 780

VIS NIR

Expanding VIS techniques to NIR



Channel 1 Channel 2 Channel 3 Channel 4 Channel 5

1) Reflectance reconstruction system


1000 nm)



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1000 nm)

Food

Wood Leather

Plastics

Fabrics

Marble

Plants

Paper, cardboard…

80 samples

(natural and manufactured)



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1000 nm)

WIENER (Transformation 1)

Wavelength (nm)

750 800 850 900 950 1000 1050

Sp

ectr

al re

flecta

nce

0.0

0.2

0.4

0.6

0.8

1.0

Fabric (original)

Fabric (reconstructed)


Wavelength (nm)

750 800 850 900 950 1000 1050

Sp

ectr

al re

flecta

nce

0.0

0.2

0.4

0.6

0.8

1.0

Red pepper (original)

Red pepper (reconstructed)


Wavelength (nm)

750 800 850 900 950 1000 1050

Sp

ectr

al re

flecta

nce

0.0

0.2

0.4

0.6

0.8

1.0

Fabric (original)

Fabric (reconstructed)


Wavelength (nm)

750 800 850 900 950 1000 1050

Sp

ectr

al re

flecta

nce

0.0

0.2

0.4

0.6

0.8

1.0

Red pepper (original)

Red pepper (reconstructed)

Prec > 99.9 % & RMSE < 1


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Wavelength (nm)

400 450 500 550 600 650 700

Rela

tive S

pec

tra

l S

en

sit

ivit

y

0.0

0.2

0.4

0.6

0.8

1.0

1.2 R Channel

G Channel

B Channel

QImaging

QICAM Fast1394

12 bit cooled

Nikon AF

Nikkor

28 – 105mm

RGB Tunable

Filter

QImaging

QICAM Fast1394

12 bit cooled

Nikon AF

Nikkor

28 – 105mm

RGB Tunable

Filter

7-channel camera

QImaging

QICAM Fast1394

12 bit cooled

Nikon AF

Nikkor

28 – 105mm

Motorized

Filter Wheel

QImaging

QICAM Fast1394

12 bit cooled

Nikon AF

Nikkor

28 – 105mm

Motorized

Filter Wheel

Wavelenght (nm)

400 450 500 550 600 650 700 750

Sp

ec

tra

l T

ran

sm

itta

nc

e

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

F400

F450

F500

F550

F600

F650

F700

RGB camera


Multispectral system in the visible range (380 -

780 nm)



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780 nm)

CCCR –

training & test

CCDC –

training & test

mean DE 3.91 3.02

min DE 0.46 0.47

max DE 14.91 9.70

Mathematical method: PSE

Number and features of the acquisition channels: 7 channels

Training and

Test

Color Rendition Chart (CCCR) DC Chart (CCDC)

Training and

Test


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780 nm)


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Pladellorens et al. Skin Res Appl 2008



780 nm)


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Wavelength (nm)

400 440 480 520 560 600 640 680 720 760

Sp

ectr

al re

fle

cta

nce

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Vilaseca et al. Appl Opt 2008

Herrera et al. Col Res Appl 2011



780 nm)


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Multispectral system in the UV-VIS-IR range

composed of light-emitting diodes (LEDs)

Near UV-Vis-NIR (350-900nm) IR (900-1700nm)

Spectral

emission

900 1000 1100 1200 1300 1400 1500 1600 17000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Wavelength (nm)

Arb

itra

ry U

nits

Emission spectra for module 2

300 400 500 600 700 800 900 10000

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Wavelength (nm)

Arb

itra

ry U

nits

Emission spectra for module 1


Martínez et al. J Imaging Sci Technol (accepted 2011)


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Near UV-Vis-NIR (350-900nm) IR (900-1700nm)

Imaging

Sensors

QICAM CCD HAMAMATSU InGaAs

Spectral

sensitivity

300 400 500 600 700 800 900 10000

0.2

0.4

0.6

0.8

1

Wavelength (nm)

Spectr

al S

ensitiv

ity

800 1000 1200 1400 1600 18000

0.2

0.4

0.6

0.8

1

Wavelength (nm)

Spectr

al S

ensitiv

ity





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Senserrich & Font 2009


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Applications in the automotive sector

Spectral and color information pixel by pixel

(Multispectral image)

Low cost: digital camera, filters, LEDs etc.

High speed: many spectra from one single measurement

(or few)

Benefits of multispectral systems:

XYZ CIE-Lab


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Potential applications:


Conventional color (CIELAB) characterization of

materials used in the automotive sector: paints, plastics

etc. E.g.: Quality control.

But also SPECTRAL! (Avoiding metamerism, color fakes

etc.)


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Multi-angle spectral and color characterization of gonio-

chromatic materials: metallic and pearlescent colors,

interference pigments etc.

E.g.: Analysis of CIELAB at different angles (15° / 25° / 45° /

75° / 110° / -15º)

Analysis of texture (sparkle, graininess and mottling effects).


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Characterization of three-dimensional (3D) samples

E.g.: Planar and curved samples

To expand the spectral information beyond the visible

(VIS) range: UV (Ultraviolet) and IR (Infrared).

E.g.: Fluorescent pigments, detection of color replicates etc.


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Our current goal (UPC-UA):

Development of a gonio-multispectral system in

the UV-VIS-IR range (250-1700 nm) based on

light-emitting diodes (LEDs)



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Our current goal (UPC-UA):

Development of a gonio-multispectral system in

the UV-VIS-IR range (250-1700 nm) based on

light-emitting diodes (LEDs)


Automated system with diffuse & directional illumination

geometries:

- 6 aspecular viewing angles (15° / 25° / 45° / 75° / 110° / -15º)

- 3-angle circumferential illumination, 1-angle viewing geometry

http://www.byk.com http://www.konicaminolta.com

http://www.byk.com/

http://www.konicaminolta.com/about/research/core_technology/optical/instrument_001.html


Hyperspectral systems

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Imaging spectrograph + monochrome CCD camera

Camera with a diffractive element:



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Scene Spatial axis

λ

Image

Scanning of the scene


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Spectral analysis of samples with complex spatial patterns:




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e-mail: [email protected]

CD6

GRACIAS !

Centre for Sensors, Instruments and Systems Development (CD6)

Dept. of Optics and Optometry

TECHNICAL UNIVERSITY OF CATALONIA (UPC)

TERRASSA

POTENTIAL OF MULTISPECTRAL TECHNIQUES FOR …...Potential of multispectral techniques for measuring...

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