Lines detection

edit

clustering the results to 13 centers ? seems like a good idea, did you try that ?

There should be 14 centers, since there are 14 segments. The main problem is that I don't know how to deal with object lines. For sure I know how iterate each line to get start/end points

Point pt1 = new Point();
Point pt2 = new Point();
double[] data;      
for (int i = 0; i <lines.rows(); i++){
    data = lines.get(i, 0);
    pt1.x = data[0];
    pt1.y = data[1];
    pt2.x = data[2];
    pt2.y = data[3];
    Imgproc.line(result, pt1, pt2, new Scalar(0, 255, 0), 1);
}

but that said I am stuck ...

kmeans, dbscan, em, chinese_whispers, partitioning, did you try any of that ? (i still think, clustering is a good idea) (tried, poor results)

there is an additional complexity thay I omitted. I have a set of images (the one I posted is just an example), each could have a different number of centers. For kmeans it think centers should be known before. What is chinese_whispers ? never heard before

Hi, my suggestion is clustering too... But I recommend that you use "superpixel", like SLIC. The SLIC will automatically figure out the centroids in a degree of "understanding the image".

Here is the comparision between some superpixel methods:

Hi, my suggestion is clustering too... But I recommend that you use "superpixel", like SLIC. The SLIC will automatically figure out the centroids in a degree of "understanding the image".

Here is the comparision between some superpixel methods:

thanks moHe. Do you have concrete example ?

I tried dbscan using Apache Maths. I am able to cluster centers of Houghlines, but I am not able to return back to lines from my clustered points.