From 169dc9c31116897cbe1237bfc11ecd31e953d5a7 Mon Sep 17 00:00:00 2001 From: Nick Yang Date: Sat, 13 Apr 2019 00:32:08 +0800 Subject: [PATCH] Merge pull request #14297 from shxuy:patch-1 fix just a typo of the word 'word' (#14297) --- .../py_histogram_backprojection/py_histogram_backprojection.markdown | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/doc/py_tutorials/py_imgproc/py_histograms/py_histogram_backprojection/py_histogram_backprojection.markdown b/doc/py_tutorials/py_imgproc/py_histograms/py_histogram_backprojection/py_histogram_backprojection.markdown index 02b0517..a235617 100644 --- a/doc/py_tutorials/py_imgproc/py_histograms/py_histogram_backprojection/py_histogram_backprojection.markdown +++ b/doc/py_tutorials/py_imgproc/py_histograms/py_histogram_backprojection/py_histogram_backprojection.markdown @@ -15,7 +15,7 @@ histograms**. **What is it actually in simple words?** It is used for image segmentation or finding objects of interest in an image. In simple words, it creates an image of the same size (but single channel) as that of our input image, where each pixel corresponds to the probability of that pixel belonging to -our object. In more simpler worlds, the output image will have our object of interest in more white +our object. In more simpler words, the output image will have our object of interest in more white compared to remaining part. Well, that is an intuitive explanation. (I can't make it more simpler). Histogram Backprojection is used with camshift algorithm etc. -- 2.7.4