How to choose the right image filtering technique for my application

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I am observing two droplets, one with a air bubble and one without an air bubble. The droplets are frozen and I watch the freezing process and track through time. Currently I send my black and white video (a snippet of it is attached as image.png) through an edge-detection filter in Matlab this filter is as follows:
B = edge(Frames,'canny',0.1);
The only problem with this "canny" method of filtering is that they leave too much noise inside the droplets, especially in the one with an air bubble. When I analyze with these filters, the noise interferes with my analysis of the freezing line and skews my data. As you can see in the "withotu bubble.PNG" file there is some noise around the freezing line and this noise is much worse in the "withairbubble.PNG" file that is attached. I want to know if there is a way for me to either remove or avoid all that noise surrounding the lines and only filter in the freezing line as it goes up.

Answers (1)

Image Analyst
Image Analyst on 19 Mar 2018
Then don't use edge detection. I see no reason why you'd want to use edge detection. And why can't you just throw out any droplets that have a bubble in them? Why even bother with them? Can't you just take another video, or not start recording if you see a bubble? Just record enough videos so that you have enough good videos even when you throw out the bad ones with air bubbles.
  11 Comments
user
user on 26 Mar 2018
No, my video has two droplets side by side, one with air bubble and one without; but that shouldn’t cause too many problems because I end up cropping the video into half and then analyzing each droplet individually.

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