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Auto-Palynology

Auto-Palynology. AutoStage Presented by Gary Allen. Representing the Pollen Research Group Massey University. Pollen – Why bother?. SEM. 81 counting stations in North America mostly manned by volunteers for advisements of airborne pollen to inhalant allergy and asthma sufferers

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Auto-Palynology

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  1. Auto-Palynology AutoStage Presented by Gary Allen Representing the Pollen Research Group Massey University

  2. Pollen – Why bother? SEM • 81 counting stations in North America mostly manned by volunteers for advisements of airborne pollen to inhalant allergy and asthma sufferers • 30 months of microscope work for a PhD student using palynology • Identification and verification of type and origin of honey • Forensic Palynology • Answer: to take the laborious and time consuming work out of palynology.

  3. Palynology – the study of Pollen SEM • Pollen: multinucleate gametophyte generation of flowering plants • 10 – 100 microns diameter • Outer wall is very durable • Textural features20 microns down to nanometresResolution achieved 1 micron Birch Grass Pine AutoStage

  4. AutoStage Flow • The study of Pollen • The system developed • The Stage • Lighting • Microscopes • Auto-focus • Segmentation • Features • Classification • Results

  5. AutoStage Flow Extraction of mathematical features Classification using MLP User adjustment of counts Display of grouped pollen

  6. The Stage • Two linear movements in the horizontal plane and orthogonal to the optical axis • Stepper motors/driver 1.8°steps and 1/10th micro-steps 2.6 microns per step of linear movement

  7. Lighting • Quartz-halogen • Transmission lighting • Band pass filtered • Yellow/green (~550nm) • Diffusing filter with opaque blocks • Dark Field illumination • Non-coherent lighting • Constant • location & intensity

  8. Microscope design • Design investigation by Craig Holdaway in his Masters project • Two microscopes: high magnification & low magnification • High magnification 11.2x • Provides 0.4 microns per pixel, sufficient to make use of the one micron resolution • produces images fit for feature extraction • Low magnification 1x • wide field of view for locating objects rapidly • sufficient depth of field to cover the slide without refocus • Firewire & USB serial connections to PC High Magnification Microscope

  9. Auto-Focus • Low magnification – performed once only • standard deviation function • High magnification – performed for each object found • maximum gradient squared function • Local peak algorithm to detect peaks in focus array Focus through entire slide Focus through pollen

  10. Segmentation Edge detection – “canny” Original image Dilate & fill • Bounding rectangle • Convex hull • Tests for pollen • Aspect ratio • Area ratios Erode Remove non-pollen

  11. Features used for discrimination • 43 features determined by Dr. Zhang & Prof. Hodgson within the pollen research group at Massey University • Textural features: • A series of Wavelet transforms that measure localised spatial, spatial‑frequency content using Gabor and Orthogonal Wavelet transforms. • Orientation sensitivity is reduced by averaging the resultscorresponding to different directions • Grey Level Co‑occurrence Matrix • Grey Gradient Co‑occurrence Matrix • Other features: • Shape, histogram, and second-moments features

  12. Classification using a neural network • Multi Layer Perceptron • Feed-forward multi-layer • back-propagation using sum of squares error • NETLAB algorithm (Ian Nabney) • No. of Inputs = No. of Features (43) • One hidden Layer with 2*n+1 hidden nodes • No. of Outputs = No. of Pollen types + detritus

  13. Results: 6 pollen on one slide

  14. QUESTIONS

  15. Results: 6 pollen on four slides

  16. Results: 6 pollen on one slide

  17. Results: 6 pollen on four slides

  18. The importance of palynology • Aeropalynology • Counts of pollen in air for agriculture, horticulture and for advisements to inhalant allergy and asthma sufferers • Palaeopalynology • The sporopollenin pollen outer wall is extremely durable and found in sediments deposited millions of years ago. By identifying pollen taxa, inferences about historical vegetation and climates can be made • Melissopalynology • The study of honey-bee pollen to determine the origin of honey. • Forensic palynology • Pollen identification in criminal forensics determines where an object has been geographically. Information about a victims last meal and where it was eaten can be obtained

  19. Results: 6 pollen on one slide

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