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INDI Library v2.0.6 is Released (02 Feb 2024)

Bi-monthly release with minor bug fixes and improvements

New Bahtinov Mask Assistant Tool

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The Bahtinov tool in APT is a licensed version of Bahtinov Grabber. The original allows the bounding box to be freely sized. The tool in APT has a rather small fixed capture area. If this is imposed by ROI limitations is not known.
Having the bounding box scaleable is useful if zoomed in images.
4 years 2 months ago #47880

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The FITS viewer in KStars contains controls to zoom in and out without resizing the capture area. To my best of knowledge it is possible to zoom in and out in the DSLR viewer as well using a mouse but I never got that to work over VNC using a MacBook trackpad.


Wouter
4 years 2 months ago #47883

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Did you look at the Muskulator app I posted earlier?
www.indilib.org/forum/ekos/4547-new-baht...l.html?start=0#34600
4 years 2 months ago #47891

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Thank you all for the interest in my (hobby)work.

I have looked at the Muskulator app. That was my inspiration for my research. Unfortunately only the executable is available I could not find the source code or an explanation of the mathematics used in this app. Looking at the files in this app shows that FFT (Fast Fourier Transformation) is used and probably some Fresnel calculations as the name of the app is called Fresnel. But that's about all I could get from this app.

If someone knows a site where diffraction pattern calculations are explained for Bahtinov masks, the I would be really interested.


Small update on the progress of the Bahtinov assistant in KStars/Ekos. I had a clear night yesterday and found out that the detection of the diffraction pattern is not working yet. So I will continue with it to make it working.
4 years 2 months ago #47910

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Not too much knowledge. What they use is so-called light propagation using FFT methods. Contrary to raytracing, that allows for diffraction effects. There used to be a (free) software called light pipes (IIRC) doing this. I just searched for it, and found that there is an implementation for Python in the package opticspy . Maybe that gives you a start.
4 years 2 months ago #47916

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Thanks for the feedback. I have cloned your repo and I am building KStars as we speak. Is there anything specific that you would like me to test or any logs or images that I can provide you with?

EDIT: I finished compiling and started up KStars. There is no algorithm Bahtinov. Only Polynomial and Iterative. Am I doing something wrong?


Wouter
Last edit: 4 years 2 months ago by Wouter van Reeven.
4 years 2 months ago #48023

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Hi Wouter,

You probably don't see my changes because I have not yet merged my changes into the main branch. I have created a branch called 'bahtinov-mask-focus' in my kstars repo. If you check out this branch, then you will have my changes.
$ git branch bahtinov-mask-focus
$ git checkout bahtinov-mask-focus
$ git pull origin bahtinov-mask-focus

Here are globally the changes I made:
The in kstars/kstars/ekos/focus/focus.ui there is a combobox called focusDetectionCombo. This should have an extra value named Bahtinov Mask. In kstars/kstars/fitsviewer/fitsdata.cpp is the implementation of the bahtinov algorithm. And in kstars/kstars/fitsviewer/fitsview.cpp is the drawing of the lines on the image. Some extra parameters have been added to the Options class.

I am a little short on time this week to develop, but hope to get some time for it next week.
There is not much logging in the code, I usually test it visually by aiming at a star, with your bahtinov mask in place and then get the image in kstars. Then see if the focus module draws the right lines on top of the image.
I found out last week that that is not the case. Some lines are drawn, but they don't make sense. Probably because the lines are not detected right. It could also be that the coordinates for drawing the lines are incorrect, but I have to look into that some more. Printing the variables of the detected lines will usually help to see if the detection did work.
I have saved the images I captured and am feeding them into my example application (which I didn't share on github yet) which uses the exact same algorithm. I noticed that the example application had a really hard time recognizing the lines in the images because the image was too noisy. I have been tweaking the few parameters I have, but they seem to be quite different for each image I feed it.
So currently I am trying two things:
  1. add some sort of algorithm to analyse the data an determine the best values for the parameters
  2. implement a completely different algorithm to detect the lines in the image
The current line detection is as follows:
  1. start processing the image the same way as it is done in the Canny algorithm that was already implemented, namely get the image data and apply a MEDIAN and HIGH_CONTRAST mask
  2. apply sobel algorithm (determine horizontal, vertical and diagonal edges)
  3. apply thinning algorithm (sharpen the edges)
  4. apply threshold (make it a 3 color image: black, 50% grey and white)
  5. apply hysteresis (make it a black and white image)
  6. apply hough transform which gives back an array of lines detected in the image
  7. take the 3 brightest lines and use them to determine the focus offset
    .1) sort the lines in order of angle
    .2) determine the intersection between the two outer lines
    .3) determine the distance between the intersection of the outer lines and the middle line, that is the offset
  8. place the data for drawing the lines in the BahtinovEdge class (derivative of Edge class used for drawing the focused stars)
  9. use the BahtinovEdge class to draw the lines on the image (in fitsview.cpp)

The alternative algorithm I was thinking off is the same algorithm used in the bahtinov-grabber application. Namely take the image, rotate it 180 degrees in steps of 1 degree en for each step calculate the average brightness of each horizontal line. When there is a diffraction line in the image positioned horizontally, then the average brightnes of that horizontal line will have a higher value. Store the highest value in an array.
After all rotation steps have been done, determine the three highest values in the array, these should be the three diffraction spikes of your bahtinov mask.
Then the processing continues from step 7 as described before.

I am also trying to apply a gaussian blur filter instead of the MEDIAN and HIGH_CONTRAST mask and see if that makes a difference.

I hope this information will help you on your way.

Kind regards,
AstroRunner
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4 years 2 months ago #48038

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"I am a little short on time this week to develop, but hope to get some time for it next week.
There is not much logging in the code, I usually test it visually by aiming at a star"


You might consider making a simple artificial star. As simple as a light source in a box with a pin hole into some aluminium cooking foil. Along with a short telescope like a spare finder/guider scope or even a camera you now have a controlled source without the vagueries of the weather or indeed time of day since It is important to keep FL short if you need a short subject to camera distance for use indoors for example.
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Last edit: 4 years 2 months ago by Rob.
4 years 2 months ago #48039

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Thanks for the extensive explanation @AstroRunner! I have checked out your branch and recompiled KStars. Now I indeed see Bahtinov in the Detection drop down. I'll try to give it a go as soon as possible.


Wouter
4 years 2 months ago #48042

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AstroRunner, I have sent you a PM.
4 years 2 months ago #48056

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Hi all,

I have finally finished the implementation of the Bahtinov Mask Focus Assistant in KStars/EKOS.
It is currently (April 2020) in review and I hope it will be integrated in the official KStars software soon.
At this moment you can get the latest version of the Bahtinov Mask Focus Assistant from my forked KDE/kstars branch: github.com/prmolenaar/kstars
Just take the master branch, build it and you have the Bahtinov Mask Focus Assistant in kStars.
Good luck and have fun testing it.
Let me know if you need some adjustments, then I can pick that up.

Best regards and clear skies!
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3 years 11 months ago #52222

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I see it, but could you provide some more steps in out to get this? What to download, command lines to build? I know... if I don't know this then I pretty much should stay away.

I'm really looking forward to this feature.
1. At this time what I do, it put the mask on, select the filter I want (normally starting at the top)
2. Take a quick 5 second shot, (that loads the filter and the focuser moves to the previous night's position)
3. Click the video icon, move the video panel to the side
4. Enter the Focuser Module, make my adjustments, once the mask is correct I enter that value in a spreadsheet that calculates the offset that I enter into the "Funnel" icon.
5. I do that for each filter.

Oh and then I forget to take off that mask when I align (haha, yeah it happens more than it should) :P

I'll make a little video tonight showing the actions.
Last edit: 3 years 11 months ago by David Tate.
3 years 11 months ago #52232

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