How to get the both uncontiguous objects in an image as just an object

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i want to loop a word in image, so that i can take every character in that image. but if i use the third dimension of bwlabel as my limit loop, the character like "i" will assume as 2 characters. because it has 2 uncontiguous object in that image. i think i have found how to get all characters of "Nick" by cropped those character automatically. but i confuse how to loop it so i can take every character and compare them with my training data.
Thanks before.
  3 Comments
Image Analyst
Image Analyst on 23 Dec 2018
Why are you doing edge detection and dilation??? That certainly doesn't make it easier to separate the characters. Don't do that!

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Accepted Answer

Image Analyst
Image Analyst on 23 Dec 2018
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 long g;
format compact;
fontSize = 20;
grayImage =imread('Adok_karo1_biner.jpg');
% Show image
figure(1)
h1 = subplot(4, 12, 1:12);
imshow(grayImage);
impixelinfo
title('INPUT IMAGE WITH NOISE')
%% Convert to gray scale
if size(grayImage, 3) == 3 % RGB image
grayImage=rgb2gray(grayImage);
end
%% Convert to binary image
threshold = graythresh(grayImage);
binaryImage = im2bw(grayImage, threshold);
% Remove all object containing fewer than 15 pixels
binaryImage = bwareaopen(binaryImage,15);
imshow(binaryImage);
axis('image', 'on'); % Display tick marks.
title('Binary Image', 'FontSize', fontSize);
% Find horizontal profile
h2 = subplot(4, 12, 13:24);
horizontalProfile = sum(binaryImage, 1);
plot(horizontalProfile, 'b-');
title('Horizontal Profile', 'FontSize', fontSize);
grid on;
% Find dividing lines between the characters.
props = regionprops(horizontalProfile == 0, 'Centroid');
xyCentroids = [props.Centroid];
dividingLines = xyCentroids(1:2:end)
for k = 1 : length(dividingLines)
thisX = dividingLines(k);
line(h1, [thisX, thisX], ylim(h1), 'Color', 'r');
line(h2, [thisX, thisX], ylim(h2), 'Color', 'r');
end
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'Outerposition', [0, 0.05, 1, 0.95]);
drawnow;
% Extract each letter.
fontSize = 12;
for k = 1 : length(dividingLines) - 1
thisX = round(dividingLines(k));
nextX = round(dividingLines(k+1));
subplot(4, 12, 24 + k);
thisLetter = binaryImage(:, thisX:nextX);
imshow(thisLetter);
caption = sprintf('Letter #%d', k);
title(caption, 'FontSize', fontSize);
end
0000 Screenshot.png
Note that if you have kerning, like with characters 3 and 5, this algorithm won't work and you will have to do a little more work, like label the sub image and if there are two blobs, find their centroids. If there centroids are horizontally separated, then they're two kerned characters and you can nsplit them apart with ismember(). If the centroids are vertically aligned or close to it, then you might consider it as one character that has two parts like an i or j.
  9 Comments
Bachtiar Muhammad Lubis
Bachtiar Muhammad Lubis on 3 Jan 2019
thank you Image Analyst it worked perfectly. do you wanna help me to answer my new question sir. the question related with this question. This the link is :
thanks a lot sir.

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