# what is exactly MultiScale hough transform (setting inputs and compare runtime between SHT & MHT)

I'm working on Line detection using OpenCV and when I saw Multi-Scale hough transform I read some papers about this algorithm and I see Multi-Scale algorithm used to large image.The original paper said that when we working with a large image the SHT parameters can increase dramatically. So I wrote a program to test (proof) it. I resize my image to be a large one but I see that SHT( the standard form of HT) is so faster than MHT

 Mat image = imread("/home/saeed/Desktop/desktop/s.png",IMREAD_GRAYSCALE);
resize(image,image,Size(1024,1024);

//MHT form
HoughLines(img,contours,1,CV_PI/180,100,0.03,1); //this line give me 2.45 sec

//SHT form
HoughLines(img,contours,1,CV_PI/180,100);    //this line give me 0.01sec


And so I think if I work on a real-time application the SHT method is a better choice (is this correct?)

And my second question. How could we set MHT inputs (SRN and STN)? I guess we should randomly select them and if the output is good then keep them!! I know these parameters for refining results so I choose every possibilities of this two parameters but MHT and SHT give me same results except in detecting lines that them angle and rho is very close.

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