5th Intensive Course on Soil Micromorphology Naples 2001 12th - 14th September Image Analysis...
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Transcript of 5th Intensive Course on Soil Micromorphology Naples 2001 12th - 14th September Image Analysis...
5th Intensive Course on Soil Micromorphology
Naples 2001
12th - 14th September
Image Analysis
Lecture 5Thresholding/Segmentation
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
basic interactive methods
•manual editting
•removal of isolated “Noise” pixelsusing SigmaScanusing HIT/MISS filters.
pre-use of low-pass filters to overcome illumination problems
Thresholding:
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
From Lecture 3: Optimum threshold occurs at minimum in intensity histogram
•But minimum not always present
•when it is, non-uniform illumination or other illumination issues can prevent ideal segmentation and editting is needed
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Often individual particles may touch
Or features have “holes” in them caused by illumination problems
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
using Sigmascan
•manually using Sigmascan•other software using feature analysis facilities
[lecture 7 will cover feature analysis in depth]
Separating touching particles:
manual approach - used in this course
A problem:
When is a particle one particle or two touching particles?
Removing “holes”
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
a)
f)e)d)
c)b)
Which, if any, of above are considered as touching particles, and which are single particles?
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Filling Holes - SigmaScan Method - Step 1
Select best threshold manually
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Filling Holes - SigmaScan Method - Step 2
Edge particles are not filled
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Filling Holes - SigmaScan Method - Step 3
Remove edge features
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•threshold image in manner covered in practical yesterday
•display threshold in say RED overlay
•use OVERLAY/MATHS - Fill Holes option
•if required use OVERLAY/MATHS - Delete Edge objects
Removing holes - Sigmascan - summary
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•Threshold image as well as possible
[particle white/background black]
•Use particle/feature analysis program
•Select background, and specify minimum area of feature to be much larger than largest hole.
•This should identify only background and not holes.
•Makes background white and particles black
•Negate image so that particles are now white
Alternative Approach:where analysis is NOT done in overlay plane:
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Manual Editting - to separate particles - step 1
Check drawing mode overlay is green
[measurements/settings/overlays].
Also check pen thickness is 3 pixels
Use annotation tool to draw separation
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Manual Editting - to separate particles - step 2
Annotation will normally be more than needed, so we need to identify the region which has both the green and red overlay i.e. blue in figure.
Select OVERLAY/MATH and options as shown.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Manual Editting - to separate particles - step 3
Blue shows where breaks should be - so above OVERLAY/MATH option will only show where particles are and not join.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Problem where thresholding leaves small isolated pixels.
Where software has facilities for HIT and MISS transform, this may be used.
With SigmaScan the following may be used.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Threshold image into overlay RED
OVERLAY/Filters as above gives image at bottom left - i.e. and erosion has reduced size of large particle, but removed small isolated pixels
NOTE: this is equivalent to normal erosion
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Using original RED overlay again.
OVERLAY/Filters as above gives image at bottom left - i.e. boundary of large particle is highlighted.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
With image at top left: OVERLAY/Maths
Select options as above - i.e.where overlay is either green or blue colour output yellow.
YELLOW overlay has desired result.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
In this example the output image is determined by multiplying the pixel value in question by 2 and all the 8 neighbouring ones by 1.
The kernel may be any size from 1 pixel up to almost any size, but many analysis facilities limit overall size (e.g. SigmaScan has a limit of 9 x 9 pixels).
1 1 1
1 2 1
1 1 1
Most filters operate by using a multiplier for each pixel in an area defined by a kernel.
Hit and Miss Filters: - background
78 65 64 62 61
72 70 68 60 59
70 70 66 62 60
68 72 64 61 66
72 68 61 60 62
69 66 62
69 66 63
68 65 62
78 65 64 62 61
72 70 68 60 59 69
70 70 66 62 60
68 72 64 61 66
72 68 61 60 62
78 65 64 62 61
72 70 68 60 59 69 66
70 70 66 62 60
68 72 64 61 66
72 68 61 60 62
78 65 64 62 61
72 70 68 60 59 69 66 62
70 70 66 62 60
68 72 64 61 66
72 68 61 60 62
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
Hit and Miss Filters:
In the example, the kernel is passed over a binary image. The corresponding pixels in the output image are only ste to 1 if the kernel exactly matches the image at the location.
In this example, this match only occurs for isolated “noise” pixels.
Many HIT and MISS algorithms, have the ability to directly subtract the output value from the input image and in this way isolated pixels of “noise” can be removed directly.
These operate differently and only on BINARY IMAGES
0 0 0
0 1 0
0 0 0
a typical HIT and MISS Filter
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•Smooth the image over a large radius
•may be helpful when there is non-uniform illumination which would otherwise cause problems during thresholding.
•Image has non uniform illumination:
•It may be possible to generate a blank image to subtract from original.
•Otherwise, an approximation can be used.
•Process is known as image restoration
Low Pass Filters:
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•prepare a blank slide of resin of same thickness as normal thin sections.
•Photograph under same illumination conditions as for slide of interest.
Intensity of background may not be exactly same in both images
When a calibration image is available
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•Identify the intensity in both the actual (Ia) and calibration image (Io) at several locations corresponding to background
•find the ratio (R) of these intensities Ia/Io
•Subtract from actual image R * calibration image
•This should give a good estimate of restored image - usually better than using uncalibrated approach.
NOTE: In SIGMASCAN there is no direct way to add/subtract/ multiply an image by a constant - this must be done indirectly using Image/Filter and Image/Maths
Procedure:
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•find the ratio (R) of these intensities Ia/Io as above
•Use calibration image and filter using following custom filter. Note: the divisor should be set to value 100 / R.
In this case R = 1.96
and divisor = 100/1.96 = 51
Modification to procedure for SIGMASCAN
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
when a calibration illumination image IS NOT VAILABLE.
generate image averaged over large radius
Image averaged using a filter radius of 72.
Radius must be chosen carefully and be larger than size of features of interest.
Usually some experimentation is necessary to find optimum radius
STEP 1:
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
STEP 2: subtract averaged image from original
Though not perfect, the background illumination has been suppress making thresholding much easier.
5th Intensive Course on Soil Micromorphology - Naples 2001Image Analysis - Lecture 5: Thresholding/Segmentation
•Thresholding in many cases is not easy
•Aim to get good contrast of features of interest
•Minimise problems of non-uniform illumination
•May need Manual Editing to separate touching particles or fill holes or remove noise
•Accuracy of result will depend on the segmentation and care is needed
•Subjectivity may cause problems between different operators
Concluding Remarks