Hyperspectral Imaging Technologies and Applications. 08. Nov Gion-Pitschen Gross

Transcription

1 Hyperspectral Imaging Technologies and Applications 08. Nov Gion-Pitschen Gross

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3 Agenda 1. Spectral Imaging Basics 2. Benefits of Spectral Imaging 3. Data Acquisition 4. Application Example 5. Other Applications 6. Desired Camera Characteristics

4 Spectral Imaging Basics

5 The Electromagnetic Spectrum source: author: Philip Ronan

6 The Visible Spectrum The World in Grey Monochrome

7 normalized absorbance The Visible Spectrum Human Vision Human cone sensitivity Wavelength [nm] author: Vanessaezekowitz at en.wikipedia

8 Spectral Imaging Basics - Overview Monochrome RGB Multispectral Hyperspectral Spectroscopy Spatial Information Band Numbers Spectral Information yes yes yes yes no >10 continuous No limited Yes Yes Yes

9 Benefits of Spectral Imaging

10 Benefits of Spectral Imaging monochrome R G B more information

11 Benefits of Spectral Imaging The more spectral data, the more information Differentiation of materials Identification of material characteristics Determination of water content Material composition

12 Data Acquisition

13 Hyperspectral Imaging Data Acquisition Whiskbroom Pushbroom Staring Snapshot Source: Li Q et al., Biomed. Opt. 18(10), 2013

14 Application Example

15 Application Example 3 White Powders Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp

16 Remission [%] Application Example 3 White Powders 110 Use Spectral Information Sodium Carbonate Sodium Carbonate Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

17 Remission [%] Application Example 3 White Powders 110 Use Spectral Information Natron Sodium Carbonate Sodium Carbonate Natron Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

18 Remission [%] Application Example 3 White Powders 110 Use Spectral Information 100 Powdered Sugar Sodium Carbonate Sodium Carbonate Powdered Sugar Natron Natron 20 Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

19 Remission [%] Application Example 3 White Powders Monochrome Monochrome Powdered Sugar Natron Sodium Carbonate X Sodium Carbonate Powdered Sugar Natron 20 Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

20 Remission [%] Application Example 3 White Powders Color (RGB) Color (RGB) Powdered Sugar Natron Sodium Carbonate X Sodium Carbonate Powdered Sugar Natron 20 Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

21 Remission [%] Application Example 3 White Powders Consider Infrared Powdered Sugar Sodium Carbonate Sodium Carbonate Powdered Sugar Natron Natron 20 Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

22 Remission [%] Application Example 3 White Powders SWIR SWIR Powdered Sugar Natron Sodium Carbonate X Sodium Carbonate Powdered Sugar Natron 20 Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

23 Remission [%] Application Example 3 White Powders SWIR Choose bandpass filter SWIR Powdered Sugar Sodium Carbonate Natron Source: Optotechnik und Bildverarbeitung (OBV) Christian Günther Frank Friehl Prof. Dr. Heckenkamp Wavelength [nm]

24 Sometimes a filter is all it takes Depending on task at hand, one filter can be enough Can be a small and robust solution for easy integration A hyperspectral solution reduced to one relevant bandpass

25 Spectral Remission [%] And sometimes a multi / hyperspectral solution is required Identification of recyclable plastics Separation of Recyclable Plastics Wavelength [nm] Source: Optotechnik und Bildverarbeitung (OBV) Frank Friehl Prof. Dr. Heckenkamp

26 Other Applications

27 Other Applications Food Sorting Recycling Agriculture / Aerial Sensing Farming Detection ripeness Detection of impurities, foulness Separation of plastics Waste separation Separation of building material Detection of moisture content Detection of nutrients Mineralogy Reconnaissance Space Exploration

28 Desired Camera Characteristics

29 Desired Camera Characteristics High frame rates High spectral sensitivity Low noise (read-out noise) High linearity stabilized operating conditions (TE cooling)

30 Thank you! Visit us at booth F62 Gion-Pitschen Gross Product Manager Allied Vision Technologies GmbH Klaus-Groth-Strasse Ahrensburg Germany