After applying the LBP on the images, the result of LBP histogram give you the features of the image

 A feature vector is usually generated from LBP histograms. You can use these feature vectors as an input to the classifier.  

You can get the matlab code on internet for texture extraction from the histogram of LBP.

Thanks, everyone. I will look for it.

you can use the function features = extractLBPFeatures(I) from MATLAB

try this code for LBP

http://www.iv.optica.csic.es/page49/styled-2/page60.html

Ascar Davix X Thank you. I will try it later

MATLAB 2018a, there is a commend to extract features

'extractLbpfeatures(grayimage)'

%function [ LBP ] = LBP( I2) [f,p] = uigetfile('*.jpg;*.bmp'); I = imread([p f]); I = imresize(I,[256 256]); cform = makecform('srgb2lab'); lab = applycform(I,cform); ll = lab(:,:,1); I2=ll; m=size(I2,1); n=size(I2,2); for i=2:m-1 for j=2:n-1 c=I2(i,j); I3(i-1,j-1)=I2(i-1,j-1)>c; I3(i-1,j)=I2(i-1,j)>c; I3(i-1,j+1)=I2(i-1,j+1)>c; I3(i,j+1)=I2(i,j+1)>c; I3(i+1,j+1)=I2(i+1,j+1)>c; I3(i+1,j)=I2(i+1,j)>c; I3(i+1,j-1)=I2(i+1,j-1)>c; I3(i,j-1)=I2(i,j-1)>c; LBP(i,j)=I3(i-1,j-1)*2^7+I3(i-1,j)*2^6+I3(i-1,j+1)*2^5+I3(i,j+1)*2^4+I3(i+1,j+1)*2^3+I3(i+1,j)*2^2+I3(i+1,j-1)*2^1+I3(i,j-1)*2^0; end end figure(); imshow(LBP);

how do I extract lbp feature vector after doing the above code and what feature vector are we getting ? so that I can feed this feature vector for neural classification.

just use Matlab function,

extractLBPFeatures(I,'CellSize',[32 32],'Normalization','None');

Thank you Prof. Ali

Ali Javed can you explain more regarding the cellsize? because i cant get 256 bins.

extractLBPFeatures(I,'CellSize',[32 32],'Normalization','None');

you can use this function in Matlab

features = extractLBPFeatures