Mark1988's profile - activity

@LBerger i just took a quick peek at it and i believe the problem is that if i have only one large contour in my image. since the components can be anything (not just triangle, square,...), i was thinking to use machine learning (e.g. kNN), but i stumbled against the same problem with one large contour. i guess one solution could be to try delete the lines and leave the components as separate contours, but i wouldn't know how to do that (not even eroding/dilating since the lines are of same thickness)

After you download the whole project:

1. Position yourself into KS_Traffic_Analyzer-master\ffmpeg folder and copy opencv_ffmpeg310.dll and opencv_ffmpeg310_64.dll files
2. Paste those 2 files into KS_Traffic_Analyzer-master\out\artifacts\KSTrafficAnalyzer_jar folder
3. Run KS_Traffic_Analyzer-master\out\artifacts\KSTrafficAnalyzer_jar\KSTrafficAnalyzer.jar file

That should work. The other method is to edit environment variables and put those two .dll files in the path.

Hello everyone!

Now this is something I've been trying to do for a while without real success and I would really appreciate help. I have a binary image with few components connected with lines. An example would be something like this:

What I need is to recognize all the components (in this example squares, triangles and circles) and how are they connected so the end result would be getting the coordinates of every component and every line so i can recreate it later if necessary.

My thinking is to recognize all the components first and lines later, so I would get something like this:

Then I easily store the coordinates and remove them from the picture and I get only lines:

And this part could be done with probabilistic HoughLines to get all the lines (all 10 of them).

So what I need help with is the way to go with the first part. How do I recognize my components? What is a good approach to this problem?

I would really appreciate any hint for solving this problem.