Take a text line in an image file to create a new image file MATLAB - matlab

Question

I need to take each line of text from an image file and create a new separate image for each of the lines. i already have a way to count how many lines are in the image file.
if anybody has any suggestions it would be a huge help because i'm not too good with images. im not allowed to use the image processing toolbox.
This is the code:
function out = countLines( imgFile )
% count the number of lines in the image file
im = imread(imgFile);
im = 255 - im;
imbw = uint8(0.33*im(:,:,1) + 0.34*im(:,:,2) + 0.33*im(:,:,3)) > 127;
imwrite(imbw, 'temp.jpg');
rvec = sum(imbw');
rvec1 = [0 rvec 0];
svec = [rvec 0 0];
out = sum(rvec1 == 0 & svec ~= 0);

Answer 1

I tried this method on a test image I found on the internet and it seemed to work alright provided the text is straight. Basically you look for entries in your rvec vector whose neighbouring entries are both smaller than them. That is to say you look for the local maximum entries (first image). After that you group the clusters of lines together to decide where to split the image (second image).
clear; clc;
im = imread('text.png'); % load the image
[Nrows,Ncols,~] = size(im); % get the size
imgray = rgb2gray(im); % convert to grayscale
vec = mean(imgray,2); % average intensities of each row
localMax=[]; % list of local maximum entries
for i = 2:Nrows-1 % accept local max rows that do not have text
hasText = sum( imgray(i,:)<100 )>0;
if vec(i)>vec(i-1) && vec(i)>vec(i+1) && ~hasText
localMax = [localMax;i];
end
end
numMax = length(localMax);
% get distances between local max rows
distances = localMax(2:end) - localMax(1:end-1);
thresh = mean(distances); % the average distance will be our threshold
splitRows = []; % rows where we will split the image
cluster = localMax(1); % start a cluster with the first local max row
for i = 1:numMax-1;
if distances(i) < thresh % if rows are close together, keep them in a cluster
cluster = [cluster;localMax(i+1)];
else % average the cluster to get the row where we split the image
newSplit = round(mean(cluster));
splitRows = [ splitRows ; newSplit ];
cluster = localMax(i+1);
end
end
newSplit = round(mean(cluster)); % add the last cluster as well
splitRows = [ splitRows ; newSplit ];