From 1a6b4d6ce6610e83f683f03c82fae0b40c048227 Mon Sep 17 00:00:00 2001 From: Ben Li Date: Thu, 2 Apr 2020 21:32:03 -0400 Subject: [PATCH] typo fix --- .../py_imgproc/py_houghlines/py_houghlines.markdown | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown b/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown index 17844b7e80..9851599455 100644 --- a/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown +++ b/doc/py_tutorials/py_imgproc/py_houghlines/py_houghlines.markdown @@ -80,7 +80,7 @@ Probabilistic Hough Transform In the hough transform, you can see that even for a line with two arguments, it takes a lot of computation. Probabilistic Hough Transform is an optimization of the Hough Transform we saw. It doesn't take all the points into consideration. Instead, it takes only a random subset of points which is -sufficient for line detection. Just we have to decrease the threshold. See image below which compares +sufficient for line detection. We just have to decrease the threshold. See image below which compares Hough Transform and Probabilistic Hough Transform in Hough space. (Image Courtesy : [Franck Bettinger's home page](http://phdfb1.free.fr/robot/mscthesis/node14.html) )