I am working with aragonite biominerals in the SEM and trying to analyze individual grains. I want to measure size and shape through thresholding and particle analysis.
I have worked quite a lot on sample preparation to uniformally outline individual crystals. My samples hae an anisotropic arrangement and therefore grain boundaries are better defined in x-direction than in y-direction. Here you see an unprocessed example image:
You see that some of the crystas are outlined nicely, making thresholding and particle analysis easy. However some of them are still “fused together” with only minor contrast differences seperating them. I have outlined some of the cases here:
I can’t do much more regarding sampole preparation - stronger etching will cause the other crystals to lose their form, and not help much with seperating the fused crystals. I am thinking of enhancing there fused crystals with directional filtering but I am not sure where to start.
I already preprocess the images with a median / lowpass filter to remove noise. I experimented with MorphoLibJ, using a laplacian filter and substracting the result from the original image to improve contours. While it improves the contours it is still insufficient. This is why I currently use distance transform watershed to seperate these crystals, but this involves fiddling with dynamic values which I would rather avoid to ensure reproducibility.
So I am currently at my wits end regarding improvements to the image that would allow for easy thresholding - particle analysis.
Other analysis approaches I considered are Fractal Surface Measurement - whch I don’t think is suited here; Or mean line interception - of which I can’t find an automated implementation for imagej.
So any tipps you guys might have that improve the separation of individual crystals on my example image would help me tremendously.