MATLAB: Optical character recognition for seven-segment display digit.[MATLAB]

auto croppingcropdoit4meImage Processing Toolboxrecognitionseven segment

Hi. recently i am doing on a project of Optical character recognition for seven-segment display digit. I am asked to crop out [attach photo] the A,B,C,D,E,F,G accordingly using AUTO -CROPPING.

http://i1149.photobucket.com/albums/o582/Pillowgerr/24bd59a8.jpg

and i had a hard time figuring the codes & ways succesfully do it. I hope any of you can assist me with coding and explanations. thank you so much! 🙂

Best Answer

You don't need to crop, unless you want to, or unless your segments wander all over from image to image. You segments should be in the same place in each image unless for some reason your camera is not mounted properly, or your display is bouncing around.

To check whether segments are on or off is pretty easy. Just look at the color channels to extract the segments, and look in boxes located at certain locations (the middle of where each segment is expected to be) for whether the pixels there are white or black. See my demo to get you started:

% Demo to check a 7 segment display.
% By ImageAnalyst
clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables.
workspace;  % Make sure the workspace panel is showing.
fontSize = 14;
% Read in a standard MATLAB gray scale demo image.
folder = 'C:\Users\Esther\Documents\Temporary';
baseFileName = '7segmentdisplay.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows columns numberOfColorBands] = size(rgbImage);
% Display the original color image.

subplot(2, 2, 1);
imshow(rgbImage, []);
title('Original Color Image', 'FontSize', fontSize);
% Enlarge figure to full screen.

set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Extract the individual red, green, and blue color channels.
redChannel = rgbImage(:, :, 1);
greenChannel = rgbImage(:, :, 2);
blueChannel = rgbImage(:, :, 3);
% Display the original color image.
subplot(2, 2, 2);
imshow(redChannel, []);
title('Red Channel', 'FontSize', fontSize);
subplot(2, 2, 3);
imshow(greenChannel, []);
title('Green Channel', 'FontSize', fontSize);
subplot(2, 2, 4);
imshow(blueChannel, []);
title('Blue Channel', 'FontSize', fontSize);
% Extract just the segments and not the numbers.
figure;
binaryImage = ~(redChannel < 200) & (blueChannel < 200);
% subplot(2, 2, 1);
imshow(binaryImage, []);
axis on;
drawnow;
hold on;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Now define locations to check.
row1 = 35;
row2 = 110;
row3 = 175;
row4 = 260;
row5 = 330;
col1 = 70;
col2 = 175;
col3 = 275;
% Plot boxes around there to check.
title('Checking Image Inside Red Boxes', 'FontSize', fontSize);
boxWidth = 30;
% First check top segment.
row = row1;
col = col2;
boxX = [col col+boxWidth col+boxWidth col col];
boxY = [row row row + boxWidth, row + boxWidth, row];
plot(boxX, boxY, 'ro-');
imageInsideBox = binaryImage(row:row + boxWidth, col:col+boxWidth)
% Determine if there are any pixels set inside that box.


segmentState(1) = any(imageInsideBox(:))
% Now check upper left segment.
row = row2;
col = col1;
boxX = [col col+boxWidth col+boxWidth col col];
boxY = [row row row + boxWidth, row + boxWidth, row];
plot(boxX, boxY, 'ro-');
imageInsideBox = binaryImage(row:row + boxWidth, col:col+boxWidth)
% Determine if there are any pixels set inside that box.
segmentState(2) = any(imageInsideBox(:))
% Now check lower right segment.
row = row4;
col = col3;
boxX = [col col+boxWidth col+boxWidth col col];
boxY = [row row row + boxWidth, row + boxWidth, row];
plot(boxX, boxY, 'ro-');
imageInsideBox = binaryImage(row:row + boxWidth, col:col+boxWidth)
% Determine if there are any pixels set inside that box.
segmentState(6) = any(imageInsideBox(:))

Related Solutions

MATLAB: Crop dark area and display the face only

Convert to grayscale and then threshold and find the bounding box

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
imtool close all;  % Close all imtool figures.
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format long g;
format compact;
fontSize = 20;
% Read in the color image.
folder = pwd;
baseFileName = 'm2.bmp';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
if ~exist(fullFileName, 'file')
  % Didn't find it there.  Check the search path for it.
  fullFileName = baseFileName; % No path this time.
  if ~exist(fullFileName, 'file')
    % Still didn't find it.  Alert user.
    errorMessage = sprintf('Error: %s does not exist.', fullFileName);
    uiwait(warndlg(errorMessage));
    return;
  end
end
rgbImage = imread(fullFileName);
% Get the dimensions of the image.  numberOfColorBands should be = 3.
[rows, columns, numberOfColorBands] = size(rgbImage);
% Display the original color image.
subplot(2, 3, 1);
imshow(rgbImage, []);
axis on;
title('Original Color Image', 'FontSize', fontSize);
drawnow;
% Enlarge figure to full screen.
set(gcf, 'units','normalized','outerposition',[0 0 1 1]);
% Histogram the red channel, but there is a huge spike at 255 so let's not count those.
subplot(2, 3, 2);
grayImage = rgb2gray(rgbImage);
imshow(grayImage, []);
title('Gray Scale version', 'FontSize', fontSize);
subplot(2, 3, 3);
histogram(grayImage(grayImage<255))
grid on;
title('Histogram of Gray Scale Image', 'FontSize', fontSize);
someThresholdValue = 150;
binaryImage = grayImage > someThresholdValue;
% Take largest blob
binaryImage = bwareafilt(binaryImage, 1);
subplot(2, 3, 4);
imshow(binaryImage);
grid on;
title('Binary Image', 'FontSize', fontSize);
% Label the binary image.
labeledImage = bwlabel(binaryImage);
props = regionprops(labeledImage, 'BoundingBox');
bbox = props.BoundingBox
croppedImageRGB = imcrop(rgbImage, bbox);
subplot(2, 3, 5);
imshow(croppedImageRGB);
grid on;
title('Cropped RGB Image', 'FontSize', fontSize);
% Gray scale version of cropped image
croppedImageGray = imcrop(grayImage, bbox);
subplot(2, 3, 6);
imshow(croppedImageGray);
grid on;
title('Cropped Gray Scale Image', 'FontSize', fontSize);

MATLAB: Binary Image – Black region detection

Mohsina, try this:

clc;    % Clear the command window.
close all;  % Close all figures (except those of imtool.)
clear;  % Erase all existing variables. Or clearvars if you want.
workspace;  % Make sure the workspace panel is showing.
format short g;
format compact;
fontSize = 25;
%===============================================================================

% Get the name of the image the user wants to use.
baseFileName = 'image1.png';
% Get the full filename, with path prepended.
folder = []; % Determine where demo folder is (works with all versions).
fullFileName = fullfile(folder, baseFileName);
%===============================================================================
% Read in a demo image.
grayImage = imread(fullFileName);
% Get the dimensions of the image.
% numberOfColorChannels should be = 1 for a gray scale image, and 3 for an RGB color image.
[rows, columns, numberOfColorChannels] = size(grayImage)
if numberOfColorChannels > 1
  % It's not really gray scale like we expected - it's color.
  % Use weighted sum of ALL channels to create a gray scale image.
  grayImage = rgb2gray(grayImage);
  % ALTERNATE METHOD: Convert it to gray scale by taking only the green channel,
  % which in a typical snapshot will be the least noisy channel.
  % grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the image.



subplot(2, 2, 1);
imshow(grayImage, []);
axis on;
axis image;
caption = sprintf('Original Gray Scale Image');
title(caption, 'FontSize', fontSize, 'Interpreter', 'None');
drawnow;
hp = impixelinfo();
% Set up figure properties:
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0, 0, 1, 1]);
% 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;
% Create binary image of the black blobs from grayscale image.
binaryImage = grayImage == 0;
% Get rid of the background.
binaryImage = imclearborder(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Label the blobs
[labeledImage, numBlobs] = bwlabel(binaryImage);
% Display the image.
subplot(2, 2, 2);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image', 'FontSize', fontSize, 'Interpreter', 'None');
% Let's assign each blob a different color to visually show the user the distinct blobs.
coloredLabels = label2rgb (labeledImage, 'hsv', 'k', 'shuffle'); % pseudo random color labels
% coloredLabels is an RGB image.  We could have applied a colormap instead (but only with R2014b and later)
subplot(2, 2, 3);
imshow(coloredLabels);
axis on;
axis image; % Make sure image is not artificially stretched because of screen's aspect ratio.
caption = sprintf('Pseudo colored labels, from label2rgb().');
title(caption, 'FontSize', fontSize);
drawnow;
% Make measurements of bounding box.
props = regionprops(labeledImage, 'BoundingBox');
% Display the image.
subplot(2, 2, 4);
imshow(binaryImage, []);
axis on;
axis image;
title('Binary Image with Boxes', 'FontSize', fontSize, 'Interpreter', 'None');
% Display the bounding boxes around them.
hold on;
for k = 1 : numBlobs
  thisBoundingBox = props(k).BoundingBox
  rectangle('Position', thisBoundingBox, ...
    'EdgeColor', 'c', 'LineWidth', 2);
end

Best Answer

Related Solutions

MATLAB: Crop dark area and display the face only

MATLAB: Binary Image – Black region detection

Related Question