How to compare the intensity of the central pixel with its 8 neighboring pixel in an image? Can anyone help me with its matlab code? Also I have to save my central pixel if its intensity value is greater than other pixels.
MATLAB: How to compare the intensity of the central pixel with its 8 neighboring pixel in an image? Can anyone help me with its matlab code? Also I have to save the central pixel if its intensity value is greater than other pixels.
pixel comparing with neighbor pixel
Related Solutions
Try this. Adapt as needed, like the percentage of the middle that you want.
clc; % Clear the command window.
close all; % Close all figures (except those of imtool.)
workspace; % Make sure the workspace panel is showing.
format long g;format compact;fontSize = 16;%===============================================================================
% Get the name of the image the user wants to use.
baseFileName = 'c3.jpg';folder = pwdfullFileName = fullfile(folder, baseFileName);% Check if file exists.
if ~exist(fullFileName, 'file') % The file doesn't exist -- didn't find it there in that folder.
% Check the entire search path (other folders) for the file by stripping off the folder.
fullFileNameOnSearchPath = baseFileName; % No path this time.
if ~exist(fullFileNameOnSearchPath, 'file') % Still didn't find it. Alert user.
errorMessage = sprintf('Error: %s does not exist in the search path folders.', fullFileName); uiwait(warndlg(errorMessage)); return; endend%=======================================================================================
% Read in demo image.
rgbImage = imread(fullFileName);% Get the dimensions of the image.
[rows, columns, numberOfColorChannels] = size(rgbImage)% Display image.
subplot(3, 3, 1);imshow(rgbImage, []);axis on;caption = sprintf('Original Color Image\n%s', baseFileName);title(caption, 'FontSize', fontSize, 'Interpreter', 'None');hp = impixelinfo(); % Set up status line to see values when you mouse over the image.
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0.05 1 0.95]);% Get rid of tool bar and pulldown menus that are along top of figure.
% set(gcf, 'Toolbar', 'none', 'Menu', 'none');
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off')drawnow;% Find the max in all color channels.
mask = max(rgbImage, [], 3);% Take the largest blob only, to get rid of noise.
% mask = bwareafilt(mask, 1);
% Fill any holes in it.
% mask = imfill(mask, 'holes');
% Let's assume it's supposed to be convex. Make sure.
% mask = bwconvhull(mask);
% Display the image.
subplot(3, 3, 2);histogram(mask);% Binarize the image
mask = mask > 225;% Keep only largest region then invert it to get the coin masks.
mask = ~bwareafilt(mask, 1);% Fill holes.
mask = imfill(mask, 'holes');% Get rid of blobs less than 1000 pixels. There seems to be a few.
mask = bwareafilt(mask, [1000, inf]);[labeledImage, numBlobs] = bwlabel(mask);imshow(mask, []);axis on;title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Mask the image with the new, cleaned mask.
% Mask the image using bsxfun() function to multiply the mask by each channel individually.
maskedRgbImage = bsxfun(@times, rgbImage, cast(mask, 'like', rgbImage));% Display the image.subplot(3, 3, 3);imshow(maskedRgbImage, []);axis on;title('Masked RGB Image', 'FontSize', fontSize, 'Interpreter', 'None');drawnow;% Get the equivalent bounding box.
props = regionprops(mask, 'BoundingBox', 'area');allAreas = [props.Area]plotNumber = 7;percentage = 0.15; % Percentage of coin the middle part should be.
for k = 1 : length(props) % Crop the image
croppedImage = imcrop(rgbImage, props(k).BoundingBox); % Display the images.
subplot(3, 6, plotNumber); imshow(croppedImage, []); axis on; title('Cropped RGB Image', 'FontSize', fontSize, 'Interpreter', 'None'); drawnow; % Now crop out the middle 50%
% Get the dimensions of the image. [rows, columns, numberOfColorChannels] = size(croppedImage); row1 = round(rows * (0.5 - percentage)); row2 = round(rows * (0.5 + percentage)); col1 = round(rows * (0.5 - percentage)); col2 = round(rows * (0.5 + percentage)); middlePart = croppedImage(row1:row2, col1:col2, :); % Display the images. subplot(3, 6, plotNumber + 1); imshow(middlePart, []); axis on; title('Cropped RGB Image', 'FontSize', fontSize, 'Interpreter', 'None'); drawnow; plotNumber = plotNumber + 2;end
[~, central_pixel_idx] = min( abs( bsxfun(@times, logical(YourGrayImage), 1:size(YourGrayImage,2)) - size(YourGrayImage,2)/2)) );
Best Answer