On Fri, Jul 12, 2013 at 7:13 AM, ginger wend <gingerw@walla.com> wrote:

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.htm... )? - 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.

Hi,

LBP can be quite confusing at first, but the idea is pretty simple. I recently added some more explanations to the example in the gallery (most of the addition is code to plot things---you don't really need to understand that part of the code): https://github.com/scikit-image/scikit-image/blob/master/doc/examples/plot_l... That example should clarify most of your questions. I don't really know how the boundary is treated, so maybe someone else can clarify that point. Best, -Tony