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Wind radar: Examples

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noise removal (median / averaging / adaptive filters) image restoration ... Solidity. Perimeter. Compactness. Borderline FFT (5 features related to roughness) ... – PowerPoint PPT presentation

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Title: Wind radar: Examples


1
Image Processing and Pattern Recognition
Jouko Lampinen
2
Outline
  • Image Processing
  • Case example
  • Pattern Recognition
  • Pattern recognition problem
  • Classification statistical and neural methods
  • Case examples

3
Image Processing
  • Image enhancement
  • histogram transforms (equalization / contrast)
  • noise removal (median / averaging / adaptive
    filters)
  • image restoration (blur removal)
  • Preprocessing for image analysis
  • thresholding and segmentation
  • edge detection
  • morphological filtering (opening / closing /
    skeleton)
  • Image reconstruction
  • transformations, tomography

4
Image analysis of grain material in concrete
production
  • Images captured by standard
  • 1200 dpi color scanner
  • Grain shape inputs
  • angularity, flakiness
  • Grain texture inputs
  • Boundary surface texture
  • FFT based texture features
  • Image Analysis Tool
  • Matlab standalone application
  • Quality Control Tool
  • Excel macro package for running
  • and analyzing the Bayesian
  • MLP models

5
Example of grains (1.6-2.0 mm sieve fraction)
6
Grain Features Measured from the Image
  • Area
  • Major Axis
  • Minor Axis
  • Eccentricity
  • Convex Area
  • Equivalent Diameter
  • Solidity
  • Perimeter
  • Compactness
  • Borderline FFT (5 features related to roughness)
  • Texture 2D FFT (5 features related to surface
    structure)
  • Morphological Spectrum (roundness)

7
Object size and shape characterization
  • Bounding box (rotated along principal axes)
  • Ellipsoid determined by the principal axes
  • Convex hull

8
Original sand grain image (natural sand)
9
Thresholded image (natural grains)
10
Objects filled
11
Morphological opening (yellow pixels removed)
12
Labelled objects
13
Bounding boxes and minor/major axes
14
Original sand grain image (crushed)
15
Thresholded image (crushed)
16
Objects filled
17
Morphological opening (yellow pixels removed)
18
Labelled objects
19
Bounding boxes and minor/major axes
20
Grain shape analysis angularity
Sharp angles in grains break under compression
Measurement simulate the erosion due to Ice Age
by morphological erosion
Morphological spectrum S(r) Amount of material
removed by circular structure element of radius r
21
Example of Morphological Spectra and Angularity
Natural gravel (manufactured by Ice Age)
Crushed gravel
Morphological spectrum
22
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