How to automatically identify text lines from projection plot?

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I have been reading about automatic text line recognition in Matlab and although there are many advanced methods to do this every paper mentions that the simplest way of detecting text lines is via horizontal projections. So I decided to try this method for myself.

I am very new to this and have hit a brick wall, I have reached a level beyond which I do not know how to proceed. This is what I have achieved so far:

I'm trying for a system that is language independent and only interested in text lines, so I chose Arabic text:

I used the function ``radon`` to get the projections.

    img = rgb2gray(imread('arabic.jpg'));
    [R, xp] = radon(bw_closed, [0 90]);
    figure; plot(xp,R(:,2)); title('at angle 90');

This is the plot(projection)

So clearly the 5 peaks represent the 5 lines detected but how do I go from here to segmenting the original document?

Can anyone help me beyond this point? All the papers I read make no mention of how to proceed from this step, they just say that from the projections we have our detected lines.

What I'm asking is how, from the plot data can I tell matlab what is the line of text and what is the gab between lines?

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VIBHATH V B 2015-3-3

Hi.......... Can u send me the whole code for the above? What is 'bw-closed' here? My E-mail Id is : vibhathvb@gmail.com

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Answer 1

Image Analyst 2014-1-18

在 MATLAB Online 中打开

3 个投票

I would just find where the black is in the profile

darkPixels = R < 20; % Threshold
% label
labeledRegions = bwlabel(darkPixels);
% Find centroids
measurements = regionprops(labeledRegions, 'Centroid');
% Get them into an array
allCentroids = [measurements.Centroid];

Now you can just crop out some line of text you're interested in, into a separate image:

thisLine = yourImage(allCentroids(k):allCentroids(k+1), :);

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Image Analyst 2014-1-18

在 MATLAB Online 中打开

Alright, I'll do a complete demo starting with the binary image you showed above.

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;
% Read in a demo image.
folder = 'C:\Users\Mark\Documents\Temporary';
baseFileName = 'arabic.jpg';
% Get the full filename, with path prepended.
fullFileName = fullfile(folder, baseFileName);
% Check if file exists.
if ~exist(fullFileName, 'file')
  % File doesn't exist -- didn't find it there.  Check the search path for it.
  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;
  end
end
grayImage = imread(fullFileName);
% Get the dimensions of the image.  
% numberOfColorBands should be = 1.
[rows, columns, numberOfColorBands] = size(grayImage);
if numberOfColorBands > 1
  % It's not really gray scale like we expected - it's color.
  % Convert it to gray scale by taking only the green channel.
  grayImage = grayImage(:, :, 2); % Take green channel.
end
% Display the original gray scale image.
subplot(2, 2, 1);
% Text touches the top and bottom line, so let's pad the image
% to make a black space at top so we can find the dark centroids.
grayImage = padarray(grayImage, 10);
imshow(grayImage, []);
title('Original Grayscale Image', 'FontSize', fontSize);
% Enlarge figure to full screen.
set(gcf, 'Units', 'Normalized', 'OuterPosition', [0 0 1 1]);
% Give a name to the title bar.
set(gcf, 'Name', 'Demo by ImageAnalyst', 'NumberTitle', 'Off') 
% Let's compute and display the histogram.
[pixelCount, grayLevels] = imhist(grayImage);
subplot(2, 2, 2); 
bar(grayLevels, pixelCount);
grid on;
title('Histogram of original image', 'FontSize', fontSize);
xlim([0 grayLevels(end)]); % Scale x axis manually.
verticalProjection = sum(grayImage, 2);
subplot(2, 2, 3); 
plot(verticalProjection, 'b-');
grid on;
darkPixels = verticalProjection < 5000; % Threshold
% label
[labeledRegions, numberOfRegions] = bwlabel(darkPixels);
fprintf('Number of regions = %d\n', numberOfRegions);
% Find centroids
measurements = regionprops(labeledRegions, 'Centroid');
% Get them into an array
allCentroids = [measurements.Centroid];
xCentroids = int32(allCentroids(1:2:end));
yCentroids = int32(allCentroids(2:2:end));
% Now you can just crop out some line of text you're interested in, into a separate image:
plotLocation = 12;
for band = 1 : numberOfRegions-1
  row1 = yCentroids(band);
  row2 = yCentroids(band+1);
  thisLine = grayImage(row1 : row2, :);
  plotLocation
  subplot(10, 2, plotLocation);
  imshow(thisLine, []);
  plotLocation = plotLocation + 2
end

Does that work for you?

ayushi 2016-6-2

编辑：ayushi 2016-6-2

在 MATLAB Online 中打开

sir @Image Analyst i tried this code:

h = sum(a,2);
  plot(h,1:size(a,1),'Parent',handles.axes2)
   title('HISTOGRAM OF Cropped IMAGE', 'FontSize', 15)
   % Find the dark lanes that define the zones between the lines with letters on them.
% Rather than find the letters themselves, we will find the dark spaces between the lines.
% Then we will go from the center of each one of those to the center of the next one down the page.
% Get the vertical projection by summing the image horizontally.
verticalProjection = sum(a, 2);
pause(3)
subplot(2, 2, 3);
plot(verticalProjection, 'b-');
grid on;
title('Vertical Projection', 'FontSize', 15);
% Find the dark lanes that define the zones between the lines with letters on them.
% Rather than find the letters themselves, we will find the dark spaces between the lines.
% Then we will go from the center of each one of those to the center of the next one down the page.
darkPixels = verticalProjection < 1000; % Threshold label
[labeledRegions, numberOfRegions] = bwlabel(darkPixels);
fprintf('Number of regions = %d\n', numberOfRegions);
% Find centroids
measurements = regionprops(labeledRegions, 'Centroid');
% Get them into an array
allCentroids = [measurements.Centroid];
xCentroids = int32(allCentroids(1:2:end));
yCentroids = int32(allCentroids(2:2:end));
fprintf('I found %d black spaces between the lines of text\n', length(yCentroids));

but i am not getting the proper segmented lines here I am uploading the final segmented lines image. please suggest me where i need to change the code in order to get single single line one by one please help me to correct my code and also uploading the original image along with this

Image Analyst 2018-8-7

I don't think it has a name. It's just something I thought up. Something that basic usually doesn't have a name.

Bachtiar Muhammad Lubis 2018-12-2

@ HJ Akhtar : i've read some papers and found that this is projection profile algorihm. just googling "image segmentation using projection profile".

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Answer 2

fawzi 2014-9-25

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test.jpg

what if the lines are curved ? in this case the projection is not useful. Can you help me in this problem

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Answer 3

Rinku 2015-1-2

编辑：Walter Roberson 2015-12-19

在 MATLAB Online 中打开

0 个投票

try this code;

img = rgb2gray(imread('arabic.jpg'));
[R, xp] = radon(bw_closed, [0 90]);
figure; plot(xp,R(:,2)); title('at angle 90');
r = R(:,2);
r=r(92:391); % your image region
blank = r < 3; % region without text
[labeled, n] = bwlabel(blank);
C = regionprops(labeled, 'Centroid');  % find the centers of blank regions
for i=1:length(C)-1
    subplot(length(C)-1,1,i)
    imshow(img(C(i).Centroid(2):C(i+1).Centroid(2),:));        
end

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moahaimen talib 2017-5-7

great answering thank you i understand that now

Urooba zaki 2018-1-22

respected sir this code shows an error... i think the function file is missing ... plz reply Undefined function or variable 'bw_closed'.

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