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Public Lab Research note


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Using ImageJ to process passive particle monitor samples

by mathew |

What I want to do

I want to document the manual steps of processing the images of passive particle monitors, stepping through the first part of the process outlined in my previous note on analysis. See also: imaging passive particle monitors, replicating passive particle monitors, research background

the goal is to take a full-color microscope image and:

  • Set the scale
  • convert to a high-contrast black and white image through "thresholding"
  • fill any "holes" in the high contrast particles
  • measure the particles' perimeter and area

My attempt and results

I used Fiji, a distribution of ImageJ with a nice interface and easier scripting capabilities all ready to use.

Setting the Scale

I found instructions in the Fiji help for setting the scale.

First, draw a line of a known length (preferably on top of a calibrated scale) on one of the images using the Line Selection tool _Fiji_Is_Just__ImageJ_and_dust_documentation_and_Untitled_46.png

Screen_Shot_2015-09-18_at_4.59.06_PM.png

Now go to the menu Analyze > Set Scale.

  • Set unit length to μm (you an type um)
  • check "global"
  • this will make it apply to all the other images opened

You can find and check this calibration under Plugins > Utilities > Image Properties

Thresholding the image

Thresholding makes everything on one side of a color or lightness threshold a single color. We are going to do it on a greyscale image to get a black and white image that is "binary," i.e. every pixel is either black or white.

First, convert the image to greyscale by going to Image > Type > 8 bit

Now we want to threshold the image to a binary image. Go to Image > Adjust > Threshold

There are a variety of available modes, all of them seem to produce a decent binary image if the brightness is adjusted correctly. It is an open question as to which we should use.

Screen_Shot_2015-09-18_at_6.28.37_PM.png

select a threshold that isolates particles without including noise. This should be the same threshold used universally during processing, so some testing is called for.

Now to make sure there aren't any greyscale elements left by using the command Process > Binary > Make Binary

You should have something like this:

20xfrac_snd17-threshholded.png

Filling "Holes"

While thresholding gave us a good high-contrast image, somewhat transparent or reflective particles have "holes" inside them (left) that we want to fill (right):

Screen_Shot_2015-09-18_at_6.32.18_PM.png

Go to Process > Binary > Fill Holes

Analysis

Now our image is ready to analyze. We first need to set the measurements that will be taken. Go to Analyze > Set Measurements and check off:

  • Area
  • Perimeter
  • Shape Descriptors

Shape Descriptors will give us the "circularity" factor needed for our volume calculations.

Now go to Analyze > Analyze Particles

ImageJ has now calculated the area and perimeter of the particles and represents them as idealized ovals.

Drawing_of_20xfrac_snd17-ovals.png

We also have a .xls (Excel spreadsheet) file that we can use to run the volumetric equivalents described previously.

Questions and next steps

The manual procedure will be useful in helping us make decisions about how best to image the particles and what thresholding system to use. ultimately though, we want to create an automated script.



air-quality petcoke particulates silica pm particle-sensing particle-monitoring passive-particle-monitors passive-pm


2 Comments

I have been very fascinated by this method. I actually tried earlier today to fly my kite with pieces of tape on the flight line to "catch" particulate at altitude (like that report on salt collection using metal strips on the TALA I sent you) which immediately after getting the kite down I would put the tape on slides to seal out contaminates. Sadly the method of affixing the tape caused violent flutter and the tape wrapped itself very well. Fascinating method!! I can't wait to try it out. ImageJ is a boon for citizen science!



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