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Introduction to Static Image Analysis

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Dr. Jeff Bodycomb from HORIBA Particle presents an introduction to the technology of static image analysis for particle size and shape measurement. …

Dr. Jeff Bodycomb from HORIBA Particle presents an introduction to the technology of static image analysis for particle size and shape measurement.

This presentation is archived with the original webinar video in the Download Center at www.horiba.com/us/particle.

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  • 1. Introduction to Static Image Analysis Jeffrey Bodycomb, Ph.D. HORIBA Scientific www.horiba.com/us/particle© 2010 HORIBA, Ltd. All rights reserved.
  • 2. Why Image Analysis? Need shape information, for example due to importance of powder flow Verify/Supplement diffraction results These may have the same size (cross section), but behave very differently.© 2010 HORIBA, Ltd. All rights reserved.
  • 3. Why Image Analysis? Crystalline, acicular powders needs more than “equivalent diameter” We want to characterize a needle by the length (or better, length and width).© 2010 HORIBA, Ltd. All rights reserved.
  • 4. Why Image Analysis Pictures: contaminants, identification, degree of agglomeration Screen excipients, full morphology Root cause of error (tablet batches), combined w/other techniques Replace manual microscopy© 2010 HORIBA, Ltd. All rights reserved.
  • 5. Why Image Analysis Need shape information for evaluating packing and flow.© 2010 HORIBA, Ltd. All rights reserved.
  • 6. Effect of Shape on Flow Yes, I assumed density doesn’t matter. Roundness is a measure based on particle perimeter. θc© 2010 HORIBA, Ltd. All rights reserved.
  • 7. Major Steps in Image Analysis Image Acquisition and enhancement Object/Phase detection Measurements© 2010 HORIBA, Ltd. All rights reserved.
  • 8. Two ApproachesDynamic: Static:particles flow past camera particles fixed on slide, stage moves slide 0.5 – 1000 um 1 – 3000 um 2000 um w/1.25 objective© 2010 HORIBA, Ltd. All rights reserved.
  • 9. Dispersing a Sample Want to spread particles out so that they don’t touch (too much). No Yes© 2010 HORIBA, Ltd. All rights reserved.
  • 10. Acquiring Images We want a good microscope and nice sharp images. Pay attention to lighting and focus. No Yes© 2010 HORIBA, Ltd. All rights reserved.
  • 11. CLEMEX Multilayer Grab for Sharpness In focus Stack images for sharper final image Out of focus© 2010 HORIBA, Ltd. All rights reserved.
  • 12. Image Binarization Turn into binary image (i.e., decide what is a particle and what isn’t).© 2010 HORIBA, Ltd. All rights reserved.
  • 13. Separation© 2010 HORIBA, Ltd. All rights reserved.
  • 14. Fiber Separation Long narrow (acicular) particles tend to touch a lot. So, this is a typical problem.© 2010 HORIBA, Ltd. All rights reserved.
  • 15. Fiber Separation Separate and assign each fiber to its own bitplane.© 2010 HORIBA, Ltd. All rights reserved.
  • 16. Fiber Separation Now we are ready for analysis.© 2010 HORIBA, Ltd. All rights reserved.
  • 17. Sorting Roughness, “too rough” is red Roundness, not round enough is green© 2010 HORIBA, Ltd. All rights reserved.
  • 18. Statistics Only a few particles for this example, so the result is not useful.© 2010 HORIBA, Ltd. All rights reserved.
  • 19. Size Descriptors Equivalent Feret diam. 1 spherical diam ┴ to longest Shortest diam. Feret diam. 2 Longest diam.© 2010 HORIBA, Ltd. All rights reserved.
  • 20. Shape: Aspect Ratio Feret diam. 1Aspect ratio Fer= shortest diam et d longest diam ┴ to longest iam Shortest diam. .2= ┴ to longest diam longest diam Longest diam.= shortest Feret diam longest Feret diam= three different numbers! © 2010 HORIBA, Ltd. All rights reserved.
  • 21. More Shape Descriptors© 2010 HORIBA, Ltd. All rights reserved.
  • 22. Specification with Measurement Error Must tighten internal spec by lab error % Then product always within performance specification Allowance for Allowance for measurement measurement uncertainty uncertainty http://www.spcpress.com/pdf/Manufacturing_Specification.pdf, By David Wheeler© 2010 HORIBA, Ltd. All rights reserved.
  • 23. Effect of Number of Particles Counted 20,000 particles 200 particles “holes” in distribution second population missed But d10, d50 &d90 may appear similar© 2010 HORIBA, Ltd. All rights reserved.
  • 24. Two Kinds of Standard Deviation! Sample standard deviation is a property of the sample. It is the width of the size distribution. Measurement standard deviation is a result of the measurement and is affected by the sample standard deviation.© 2010 HORIBA, Ltd. All rights reserved.
  • 25. More particles for more accuracy. dv10 dv50 dv90 dv10 dv50 dv90 100 28.004 41.983 56.618 200 29.551 42.914 58.466 90 300 28.223 43.722 65.737 500 29.891 45.953 79.187 80 1000 29.729 46.826 79.218 2000 31.292 47.899 79.378 70 5000 5000 30.948 47.463 81.923 60 10000 31.433 48.57 81.822 20000 31.662 48.992 81.998 50 50000 31.826 49.157 83.435 100000 32.381 49.766 84.601 40 177187 32.742 49.833 83.873 30 Assume 49.833 is “correct” 20 dv50, 10 0.95 x 49.833 = 47.34 is 0 within 95%, 47.463 achieved by 5000 00 87 0 0 0 0 0 0 0 00 00 00 10 20 30 50 00 00 00 00 71 10 20 50 counts! 10 20 50 10 17 Use this to control precision of your data (and not spend extra time on precision you don’t need.© 2010 HORIBA, Ltd. All rights reserved.
  • 26. Divide Large Data Set into Smaller Sets Error bars are one standard deviation from repeated measurements of the same number of particles from different parts of the sample. The error bars get smaller as you evaluate more particles.© 2010 HORIBA, Ltd. All rights reserved.
  • 27. The HORIBA PSA300 Turnkey System More time getting results and less time engineering Automated Faster Less operator labor Less operator bias Powerful Software Features Image Enhancement Particle separation Separate Disperser Option More flexible sample preparation© 2010 HORIBA, Ltd. All rights reserved.
  • 28. Static or Dynamic Image Analysis? Dynamic Broad size distributions (since it is easier to obtain data from a lot of particles) Samples that flow easily (since they must be dropped in front of camera) Powders, pellets, granules Static Samples that are more difficult to disperse (there are more methods for dispersing the samples) Samples that are more delicate Pastes, sticky particles, suspensions© 2010 HORIBA, Ltd. All rights reserved.
  • 29. Conclusions Image Analysis is good for Size Shape Supplementing other techniques Watch out for Sample preparation Image quality Measure enough particles© 2010 HORIBA, Ltd. All rights reserved.
  • 30. Questions? www.horiba.com/us/particle Jeffrey Bodycomb, Ph.D. Jeff.Bodycomb@Horiba.com 866-562-4698© 2010 HORIBA, Ltd. All rights reserved.