Modular Processing of Hyperspectral Data - Perception Park€¦ · Hyperspectral application •...

www.perception-park.com

Modular Processing of

Hyperspectral Data

This presentation provides an insight in

technical aspects of Perception Park data

processing

Graz, Sept 25th, 2015

Markus Burgstaller

confidential www.perception-park.com

Perception Park – Who we are

2

Headquarter: Graz, Austria

We are focused on:

• Generic hyperspectral data processing

• Intuitive UI concepts and implementation

• Real-time processing

• Industrial validity


Perception Park – Who we are

3

• Motivation

• Instrumentation

• Methodology

• Application

• Products


Motivation

4

Hyperspectral technology:

• No standards available• Missing common „basis“• Elaborate interdisciplinary

cooperation

Desired Situation:• HW, SW as well as data are provided by

a community (or can be obtained from)• „Common“ operating environment ->

focus to core competence.

• Know-how encapsulation possible• Extendable• Dealing with valued data is supported


Hyperspectral Operating Environment – Layer Model

5

Layer model:

• Specialized to the needs ofHyperspectral application

• Extendable by plug-ins.

“An operating environment is usually not a full operating system but is aform of middleware that rests between the OS and the application.

For example, the first version of Microsoft Windows, Windows 1.0, was nota full operating system, but a GUI laid over DOS albeit with an API of its own.”Source: Wikipedia/Operating Environment


Hyperspectral Operating Environment


Instrumentation – Spectroscopy

7

Spectral, temporal investigation (e.g. at a specific point/area)

Spectroscopy and spectrography are terms used to refer to the measurement of radiation intensity as afunction of wavelength...

Symmetricalstretching

Antisymmetricalstretching

Scissoring

Source:http://en.wikipedia.org/wiki/Spectroscopyhttp://www.bruker.comhttp://jila.colorado.edu/


Instrumentation – Spectroscopy (cont‘d)

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UV (~0.2-0.4µm)

MWIR (~3-5µm) – InSb

VIS (~0.38-0.75µm) – Si

NIR (1.0-1.7) - InGaAsVNIR (~0.6-1.0µm) – Si

SWIR (~1.0-2.5) – MCT, InSb

SWIR (~1.2-2.2) – Ext.-InGaAs


Instrumentation - Hyperspectral Imaging

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Spatially, spectrally and e.g. temporally investigation of a region of interest.

Hyperspectral imaging, like other spectral imaging, collects and processes information from across the electromagnetic spectrum.The goal of hyperspectral imaging is to obtain the spectrum for each pixel in the image of a scene, with the purpose of findingobjects, identifying materials, or detecting processes.

Source: http://en.wikipedia.org/wiki/Hyperspectral_imaging

Wavelength

• >100 wavelengths bands

• Spatially, spectrally ande.g. temporally resolved

• Capable to applyspectroscopic techniques

• Capable to applyimage processing techniques

• at least 1D-spatial (spectral image)

www.perception-park.com 10

Spatial scanning:Line scan: Pushbroom imager

Point scan: Wiskbroom imager

Multi point scan: Multi fiber system

Spectral scanning:Wavelength scan: Staring imager

Spatiospectral scanning:Wavelength and line-scan:

wedge-filter imager

Non-scanning:one cube per time point: snapshot imager

Instrumentation - Hyperspectral Imaging (cont‘d)

Source: www.ximea.com


Instrumentation – Data Processing

11

• Calibration package• Describes the optical and electrical behavíour of

an instrument (HS camera)

• Instrument standardization (Pushbroom)• Noise suppression (filtering)• FPN-correction (dark current)

• Smile, Keystone correction• Defectpixel correction• Reduction of non-linearities

• Image registration (e.g. wavelength calibration)• Multiple ROI, Multiple Binning (Fiberoptic)

• Setup standardization• Normalization to calibration (white) target• E.g. calibration (absolute)• etc…

Transformation of sensor row data into

(best possible) standardizedHyperspectral data.


Instrumentation – Pixel Behaviour Unifying

12

Set of polymers (PP, PE, various samples of PVC)

Row data of a ExtInGAs hyperspectral camera (1200-2200nm)

Unified pixel behaviour (based on data above)

PP

PEBackground

PVC

No Filtering!!!


Instrumentation – Distortion Correction

13

No Filtering!!!


Methodology - Processing Networks

14

Data Receiver• Cameras

• Files (Harddisk)• Network Streams• etc.

Processing Block• Data Correction

• Data Manipulation• Color Models• etc.

Data Transmitter• Camera Link

• Network / GigE Vision• Application Link• etc.

Basic Module Types

CameraManufacturers

ChemometryEngineers

ApplicationEngineers

SystemIntegrators

3rd PartySoftware

3rd PartySoftware

3rd PartySoftware


Methodology – Building Networks

15

Building and extending networks

Module GroupsFactory Modules

Derive

Receiver Transmitter

Pixel Correction

Filter

DenoiseColor

Balancing

Crop

3rd Party Modules

M6

M1 M2 M3

M4 M5

Pixel Correction

Filter G2M4 M6 G4

G1 G2 G3

G4 G5 G6

Color Balancing


Methodology – Complexity Reduction

16

Workflow based User Experience

Complex processing network

Group 2Group 1

Group 3

Group 5

Group 4

Input

Output 1

Complex Networks

Output 2


Methodology - Hardware Acceleration

17

Perception Studio:

• Configure your Hardware

• Examine material properties

• Design the Processing

Network for your application

Perception System:

• Scalable Parallel Computing solution

• Example: GPU accelerated

• Runs the applied processing job

until turned off

Compile processing network for GPU

Group 2Group 1

Group 3

Group 5

Group 4

Input

Output 1

Complex Networks

Output 2


Perception Park Products

21

World’s first Hyperspectral operating

environment

In-line, at-line, on-line, off-line…

Real-time

Link between camera technology

and industrial application

To enable / push / promote Hyperspectral

Imaging in industrial environment


Perception Studio

22

Software suite for Hyperspectral data

processing

Extensible by plug-ins,

customizable

Workflows:

Setup, Acquire, Explore, Model, View, etc.

Powered by

Chemical Color Imaging


Perception System

23

Hardware to support Hyperspectral data

processing

Camera abstraction, correction and

standardization

Feature extraction –

standard imaging interfaces

Different sizes – different power –

different application


Perception System

24

Machine Vision Bridge: Prediction Engine:

Machine Vision related

solution providers

Powered by

Chemical Color Imaging

Spectroscopy related

solution providers

Support of familiar

chemometrics environment


Prediction Engine – Application Example

25

1 2

3 4

Perception Park

Perception Park

CAMO

FECOM


Acquisition of Pills (Ibuprofen)

26

Setup, Acquire, Explore, Select Spectra, Preprocess,…

1

Perception Studio


Analyzing Spectra – Modelling of Ibuprofen

27

2

The Unscrambler, CAMO Software


Real-time Prediction of Ibuprofen and Filler

28

3

Setup Prediction Engine, view prediction streams, …Perception Studio


Imaging – Analysis and Classification of Objects

29

4

Object Imaging Machine Learning Software, FECOM OG


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Modular Processing of Hyperspectral Data - Perception Park€¦ · Hyperspectral application •...

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