Discussion:
[Gwyddion-users] Calculating specific surface area
Evgeniya Khakhalova
2015-06-02 18:38:35 UTC
Permalink
Hi everyone,

I'm a new Gwyddion user and I'm trying to figure out if it is possible to
do the following:
1. I've got an MFM image of the magnetic grain and my purpose is to
calculate surface area of "light" and "dark" magnetic regions within this
magnetic grain.
"Light" domain area is where Z-component is greater than background noise,
and "dark" - where Z-component is smaller than background noise.
Is there any ways that I can calculate average background noise (areas
outside the grain) and then use it as a threshold value to mask dark/light
regions inside the grain and then calculate the surface areas of those
regions only inside the grain?

2. If it is actually possible to use crop function for some arbitrary
shapes like on the example?
3. Can I use for example respective topography image to crop the magnetic
image along its grain boundaries more precisely?

The left image on the example is Nap Phase Retrace image of the grain, the
right one is the height retrace:


[image: Inline image 1][image: Inline image 1]



Thank you.

Best regards,
Evgeniya Khakhalova.
Daniil Bratashov
2015-06-02 19:25:31 UTC
Permalink
On Tue, 2 Jun 2015 13:38:35 -0500
Post by Evgeniya Khakhalova
Is there any ways that I can calculate average background noise
(areas outside the grain) and then use it as a threshold value to
mask dark/light regions inside the grain and then calculate the
surface areas of those regions only inside the grain?
The main idea is to select region of interest by mask (by
marking grain by height threshold on height image), than to transfer
mask from height image to magnetic, and than use statistics tool on
region under/not under the mask to measure average background noise.

Than you can use threshold on magnetic image, and than use multidata
arithmetic on both masks to get intersection of two masks.
Post by Evgeniya Khakhalova
2. If it is actually possible to use crop function for some arbitrary
shapes like on the example?
Crop is not intended for such applications, better to use masks.
Post by Evgeniya Khakhalova
3. Can I use for example respective topography image to crop the
magnetic image along its grain boundaries more precisely?
Yes, by obtaining two masks and then use multidata arithmetic.

I suppose this two links will be helpful:
http://gwyddion.net/documentation/user-guide-ru/presentations-masks.html
http://gwyddion.net/documentation/user-guide-ru/multidata.html

WBR, Daniil Bratashov.

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Evgeniya Khakhalova
2015-06-04 19:36:02 UTC
Permalink
Hi Daniil,
Thank you a lot for your helpful suggestions!

To obtain the intersect of two masks I used Data Process-> Mark with->
Intersect masks.
Is the result would be the same if I'd have used multidata arithmetic as
you suggested?

And also when I use Statistical quantities for marked region it gives me
Surface area and Projected area. Do you know what is the difference between
those two and why the surface area is N.A. for magnetic images
(NapPhaseRetrace)?


Thank you!




Be well,
Evgeniya Khakhalova.
Post by Daniil Bratashov
On Tue, 2 Jun 2015 13:38:35 -0500
Post by Evgeniya Khakhalova
Is there any ways that I can calculate average background noise
(areas outside the grain) and then use it as a threshold value to
mask dark/light regions inside the grain and then calculate the
surface areas of those regions only inside the grain?
The main idea is to select region of interest by mask (by
marking grain by height threshold on height image), than to transfer
mask from height image to magnetic, and than use statistics tool on
region under/not under the mask to measure average background noise.
Than you can use threshold on magnetic image, and than use multidata
arithmetic on both masks to get intersection of two masks.
Post by Evgeniya Khakhalova
2. If it is actually possible to use crop function for some arbitrary
shapes like on the example?
Crop is not intended for such applications, better to use masks.
Post by Evgeniya Khakhalova
3. Can I use for example respective topography image to crop the
magnetic image along its grain boundaries more precisely?
Yes, by obtaining two masks and then use multidata arithmetic.
http://gwyddion.net/documentation/user-guide-ru/presentations-masks.html
http://gwyddion.net/documentation/user-guide-ru/multidata.html
WBR, Daniil Bratashov.
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David Nečas (Yeti)
2015-06-04 19:47:42 UTC
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Post by Evgeniya Khakhalova
And also when I use Statistical quantities for marked region it gives me
Surface area and Projected area. Do you know what is the difference between
those two and why the surface area is N.A. for magnetic images
(NapPhaseRetrace)?
The surface area calculation is explained here in the user guide:

http://gwyddion.net/documentation/user-guide-en/statistical-analysis.html#surface-area-calculation

Surface area makes no sense when the ‘height’ is not height but a
different physical quantity. So you can only calculate surface area for
topographical images.

Projected area is area of the base and as such can be calculated always.

Yeti


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Daniil Bratashov
2015-06-04 20:13:25 UTC
Permalink
On Thu, 4 Jun 2015 14:36:02 -0500
Post by Evgeniya Khakhalova
To obtain the intersect of two masks I used Data Process-> Mark with->
Intersect masks.
Is the result would be the same if I'd have used multidata arithmetic
as you suggested?
No problem here. The mask in general is similar to the image, where "1"
is mask and "0" corresponds to no mask regions. So mask intersection or
multiplication of two masks in multidata arithmetic should give the
similar results.
Post by Evgeniya Khakhalova
And also when I use Statistical quantities for marked region it gives
me Surface area and Projected area. Do you know what is the
difference between those two and why the surface area is N.A. for
magnetic images (NapPhaseRetrace)?
David is already answered. The surface area is area on 3D polygonal
surface (if XY and Z units are the same, else it will not be
calculated as meaningless), the projected area is the area of
projection on XY plane.

WBR, Daniil Bratashov.

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