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AFM-SPM / TopoStats

An AFM image analysis program to batch process data and obtain statistics from images
https://afm-spm.github.io/TopoStats/
GNU Lesser General Public License v3.0
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Add grain removal based on height (identify and isolate scars) #154

Closed SylviaWhittle closed 1 year ago

SylviaWhittle commented 2 years ago

Is your feature request related to a problem? Please describe. Removing anomalously high-up grains would be useful as it would remove artefacts such as scars and blobs that are not wanted and would mess with the scaling of the data.

Describe the solution you'd like A system that detects grains that are 2 standard deviations from the mean grain height and removes them.

SylviaWhittle commented 2 years ago

This maybe should go in filters as it could help with flattening

SylviaWhittle commented 2 years ago

Focus on scars as opposed to blobs

bobturneruk commented 2 years ago

See http://gwyddion.net/documentation/user-guide-en/scan-line-defects.html

bobturneruk commented 2 years ago

Image contain ~1px wide really high streaks (horizontal) - called scars. Mess up image processing and data. Need to identify and locate these features and flag them to remove if we want to. And to be able to ignore these from the flattening and grain finding process. The way forwards might be to mask out scars early on in the analysis pipeline. Maybe a separate scar mask might be good.

ns-rse commented 2 years ago

I don't know if this would be of use but I realised I had previously created #202 because I'd stumbled across the Hough Transform which is a method for identifying classes of shapes, classically straight-lines, from images.

There are methods in scikit-image that implement this (see #202 for links).

alicepyne commented 2 years ago

Would be good to have options for how many SD in the config file? In the case of including e.g. proteins which are 10x the height of DNA.

On 19 May 2022, at 13:30, SylviaWhittle @.***> wrote:

Is your feature request related to a problem? Please describe. Removing anomalously high-up grains would be useful as it would remove artefacts such as scars and blobs that are not wanted and would mess with the scaling of the data.

Describe the solution you'd like A system that detects grains that are 2 standard deviations from the mean grain height and removes them.

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