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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 learn that Multi Scale algorithm used to large image. paper said that when we working with large image HT parameter can increases dramatically.so i wrote a program to test this method and i resize my image to be a large one but i see that SHT(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 give me 2.45 sec

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

and so i think if i work on real-time application the SHT method is good choice (is this correct?)

and my second question is that how i can set MHT inputs (srn and stn)? i know this parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results.

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 learn that Multi Scale algorithm used to large image. paper said that when we working with large image HT parameter can increases dramatically.so i wrote a program to test this method and i resize my image to be a large one but i see that SHT(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 give me 2.45 sec

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

and so i think if i work on real-time application the SHT method is good choice (is this correct?)

and my second question is that how i can set MHT inputs (srn and stn)? i know this parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results.

I'm working on line Line detection using OpenCV and when i I saw Multi Scale Multi-Scale hough transform i I read some papers about this algorithm and i I learn that Multi Scale Multi-Scale algorithm used to large image. image.The original paper said that when we working with large image HT SHT parameter can increases dramatically.so i increase dramatically. So I wrote a program to test this method and i (proof) it. I resize my image to be a large one but i I see that SHT(standard 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 give me 2.45 sec

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

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

and my second question is that how i can set MHT inputs (srn and stn)? i know this parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results. results.

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 learn see Multi-Scale algorithm used to large image.The original paper said that when we working with large image SHT parameter 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 give me 2.45 sec

//SHT form 
HoughLines(img,contours,1,CV_PI/180,100);    //this 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 is that how i can set MHT inputs (srn and stn)? i know this parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results.

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

and And my second question is that how i can question. How could we set MHT inputs (srn and stn)? should we randomly select them and if theouput is good then keep them? i know this parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results.

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 SHT parameter 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)? (SRN and STN)? I guess we should we randomly select them and if theouput the output is good then keep them? i them!! I know this these parameters for refining results so i choose every possibilities of this two parameters but MHT and SHT give me same results.results except in detecting line that them angle and rho is very close.

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 I choose every possibilities of this two parameters but MHT and SHT give me same results except in detecting line lines that them angle and rho is very close.