Problem to Threshold a Matrix

2017 4 12
2 个回答
回答已采纳
更新时间：2017 4 21
2 次查看（30 天）

0 个投票

I need to threshold the surrounding pixels of the given matrix with respect to the centre pixel of the given matrix. If the surrounding values are greater than or equal to the center of the pixel they are given a 1 otherwise they are given a 0. Then I need to store all the values in the shown order to result in a vector which contains the binary value.

2 个评论
显示 无 隐藏 无

James Tursa
James Tursa 2017-4-12
Have you tried coding this? What problems are you having? Not working, or too slow, or ???
CharlesB
CharlesB 2017-4-12
matrix = [ 85 99 21; 54 54 86; 57 12 13];
%matrix(2,2) is the centre pixel
thres_mat = matrix > matrix(2,2); % which results in the binary matrix shown
my problem is to store those binary values in that order

请先登录，再进行评论。

请先登录，再回答此问题。

 采纳的回答

Image Analyst
Image Analyst 2017-4-12

1 个投票

Let's call it what it is, okay? You're asking for the " local binary pattern".
For a FULL demo on the whole image, see the attached m-file. it creates this image

6 个评论
显示 4更早的评论 隐藏 4更早的评论

CharlesB
CharlesB 2017-4-13
Simply amazing that's what I am working on the achieve :) thank you!! definitely the best answer.
CharlesB
CharlesB 2017-4-21
编辑：CharlesB 2017-4-21
Hi! I have used what you gave me to apply it to cells in a cell array where the cell array is an original image split into various cells 16x16 each. Now my problem is that the line
localBinaryPatternImage(rows, cols) = eightBitNumber;
which is found in the for loop only gives the values of the last 15x15 unit8 cell array. How can i concatenate all of the cell arrays to form the lbp image?
Image Analyst
Image Analyst 2017-4-21
You either need to extract the 16x16 image from the cell and do it on the small arrays, or just don't split the image up into cells. Not sure why you're doing that anyway.
CharlesB
CharlesB 2017-4-21
I am doing it because I want to plot the histogram and lbp features for every cell then concatenate them rather than have 1 histogram and 1 lbp feature vector for the entire image.
CharlesB
CharlesB 2017-4-21
%% Grayscale Baboon Image I2 = imread('baboon.png'); [rows,columns,dim] = size (I2); sz2 = [rows, columns];
chunk_size2 = [16 16]; % your desired size of the chunks image is broken into sc2 = sz2 ./ chunk_size2; % number of chunks in each dimension; must be integer % split to chunk_size(1) by chunk_size(2) chunks X2 = mat2cell(I2, chunk_size2(1) * ones(sc2(1),1), chunk_size2(2) *ones(sc2(2),1));
[r, c] = size(X2); z = cell2mat(X2(1));
%Extracting LBP features for each cell and concatinating them into a %histogram
% localBinaryPatternImage = zeros(size(I2), 'uint8'); %for celliter3 = 1:numel(X2)
result = []; for row = 1 : r for col = 1 : c
Z = cell2mat(X2(row, col)); [row_cell, col_cell] = size(Z);
for rows = 2 : row_cell - 1
for cols = 2 : col_cell - 1
centerPixel = Z(rows,cols);
pixel7= Z(rows-1, cols-1) > centerPixel;
pixel6= Z(rows-1, cols) > centerPixel;
pixel5= Z(rows-1, cols+1) > centerPixel;
pixel4= Z(rows, cols+1) > centerPixel;
pixel3= Z(rows+1, cols+1) > centerPixel;
pixel2= Z(rows+1, cols) > centerPixel;
pixel1= Z(rows+1, cols-1) > centerPixel;
pixel0= Z(rows, cols-1) > centerPixel;
eightBitNumber = uint8(...
pixel7 * 2^7 + pixel6 * 2^6 + ...
pixel5 * 2^5 + pixel4 * 2^4 + ...
pixel3 * 2^3 + pixel2 * 2^2 + ...
pixel1 * 2 + pixel0);
% Or you can use the built-in function bwpack(), which is somewhat simpler but a lot slower.
% eightBitNumber = uint8(bwpack([pixel0; pixel1; pixel2; pixel3; pixel4; pixel5; pixel6; pixel7]));
localBinaryPatternImage(rows, cols) = eightBitNumber;
end
end
end
end
Image Analyst
Image Analyst 2017-4-21
I don't understand why you want to do that. And anyway, you don't have one LBP feature for the entire image. Every pixel has its own local binary pattern, so you have millions of patterns.

请先登录，再进行评论。

更多回答（1 个）

James Tursa
James Tursa 2017-4-12
编辑：James Tursa 2017-4-12

2 个投票

Using your small example:
>> x = 2;
>> y = 2;
>> matrix = [ 85 99 21; 54 54 86; 57 12 13]
matrix =
85 99 21
54 54 86
57 12 13
>> t = matrix >= matrix(y,x)
t =
1 1 0
1 1 1
1 0 0
>> b = [t(y,x-1) t(y+1,x-1:x+1) t(y,x+1) t(y-1,x+1:-1:x-1)]
b =
1 1 0 0 1 0 1 1
>> d = sum(b.*2.^(7:-1:0))
d =
203

类别

在 帮助中心 和 File Exchange 中查找有关 Graph and Network Algorithms 的更多信息

产品

标签

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by