How can I extract text from image respecting the distance between words?
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I am trying to extract text from an image of printed text. Along with the text itself, I am interested in detecting the spaces between the words as well. The spaces between words are not consistent (deliberate) and that is something I want detected.
To achieved this I first had to extract the text lines. I achieved that using the projection profile code attached (code copied from one of the answers by ImageAnalyst). The attached image shows the output of this code.
One way I thought of achieving this was by counting the number of white pixels between the words, if I know the number of pixels taken by a single space (say n), I could just determine the number of spaces by dividing the white pixels between the words by this 'n' to get the number of spaces.
I tried that but it did not go as planned, the results are very conflicting, even when compared against known ground truth values. Determining a baseline of every text line is proving to be difficult, for a single space between two words I am getting different pixel count. This is because as counting the white pixels from letter d to b is different from counting the white pixels from c to s (the white pixels within the curve of c is also sometimes counted.)
Any guidance or suggestions would be greatly appreciated.
Thank you
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Ben Drebing
2017 年 12 月 18 日
Try looking at this answer:
This code can only process 1 line of text at a time. But I was able to get fairly good results on the first line of your data when I set
fontSize = 6;
2 件のコメント
Ben Drebing
2017 年 12 月 19 日
I think you can modify that Untitled2.m file to concatenate all the lines into one long line and then you can use our solution on this image. You can create a variable called "allOneLine" which has all the text but in one line. Maybe something like
img = imread('Lines.png');
[rows, columns, dim] = size(img);
if dim > 1
grayImage = img(:, :, 2);
end
% Display the original gray scale image.
% Threshold the image.
binaryImage = grayImage < 210;
% Get rid of small areaas of 14 pixels or less
binaryImage = ~bwareaopen(binaryImage, 15);
% Vertical Profile
verticalProfile = sum(binaryImage, 2);
rowsWithText = verticalProfile < 600;
% Find top and bottom lines
topLines = find(diff(rowsWithText) == 1);
bottomLines = find(diff(rowsWithText) == -1);
allOneLine = [];
for j = 1 : length(topLines)
topRow = topLines(j);
bottomRow = bottomLines(j);
thisLine = binaryImage(topRow:bottomRow, :);
allOneLine = [ allOneLine , thisLine]; % Here we append the lines
end
imshow(allOneLine); % Show our new image
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