My porblem understanding Local Binary Pattern

[ginger wend]

Hi,

I am trying to learn Local Binary Pattern with scikit-image and as I have 
only limited knowledge in numpy and image analysis I find it hard. As a 
result, I will appreciate a lot if you can provide me some answers as I am 
sure that they will help me to advance:

- If I understand correctly the skimage.feature.local_binary_pattern(image, 
P, R, method=' uniform) will go pixel by pixel (starting from pixel 
location 1,2) and generate the binary number based on the P and R, am I 
right?. If so what happens if the R is “out of boundary”?
- How do you calculate the histogram and why are there are 18 bins in the 
example 
(http://scikit-image.org/docs/dev/auto_examples/plot_local_binary_pattern.html)?
- The output is (N, M) array and when I look at it is not clear to me what 
is the output and how do you generate a histogram from it, can someone you 
please clarify it.

I know that these questions are be basic and while I was trying to look for 
answers I found the information more mathematical and less with applied 
approach. Therefore, any help, ideas or tips will help.

Thanks for the patience,
G.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20130712/1340aa4c/attachment.html>