From d03fdb8827142f62c259b9c8bcecadebcd14ed7f Mon Sep 17 00:00:00 2001 From: Vighnesh Birodkar Date: Wed, 23 Apr 2014 00:53:13 +0530 Subject: [PATCH] Corrected spellings. --- doc/examples/plot_blob.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/doc/examples/plot_blob.py b/doc/examples/plot_blob.py index a48aa418..02447ee4 100644 --- a/doc/examples/plot_blob.py +++ b/doc/examples/plot_blob.py @@ -11,14 +11,14 @@ image is a star or a galaxy, so we are literally counting stars. Laplacian of Gaussian (LoG) ----------------------------- This is the most accurate and slowest approach. It computes the Laplacian -of Gaussian images with successively increasing standard devation and +of Gaussian images with successively increasing standard deviation and stacks them up in a cube. Blobs are local maximas in this cube. Detecting larger blobs is especially slower because of larger kernel sizes during convolution. Only bright blobs on dark backgrounds are detected. Difference of Gaussian (LoG) ---------------------------- -This is a faster approximant of LoG approach. In this case the image is +This is a faster approximation of LoG approach. In this case the image is blurred with increasing standard deviations and the difference between two successively blurred images are stacked up in a cube. This method suffers from the same disadvantage as LoG approach for detecting larger