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How to find the size of the handwritten word in an image?

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Poornima Gokhale
Poornima Gokhale el 19 de Dic. de 2015
Comentada: Meghashree G el 23 de Dic. de 2015
When a word is given I want to find the size of it (not the width) i.e., if a word like 'hello' is given its approximate size should be found out considering all the upperzone letters like 'l' and middle zone letters like 'e'.I have tried the bounding box but it is not efficient because it will give the maximum possible height, but i want the average height. Please help me with the code.

Respuestas (2)

Image Analyst
Image Analyst el 19 de Dic. de 2015
To get the average height, you'll have to scan across the image column by column using find to find the first black pixel and the last black pixel
for col = 1 : size(grayImage, 2)
topRow(col) = find(grayImage < someThreshold, 1, 'first');
bottomRow(col) = find(grayImage < someThreshold, 1, 'last');
height(col) = bottomRow(col) - topRow(col);
end
meanHeight = mean(height);
  5 comentarios
Image Analyst
Image Analyst el 21 de Dic. de 2015
The app will work with either floating point images or integer images. The max threshold on the right is the highest gray level in the image I believe, or it may be the greatest value possible for integer images (I don't remember).
Integer images are typically what you read from standard format image files. You might get a floating point image if you did something like did a conversion from RGB to LAB or HSV color space, or if you summed a bunch of images and cast them to double before summing so that you would not get clipping. You should just use whatever image you have that you want to threshold.
I don't know the threshold values (low and high) that you should use. Often times it's a judgment call and that's why I built this interactive program. Sometimes you don't have a nice bimodal histogram that you can find the valley of. Sometimes it's an ugly histogram with no obvious place to threshold it at. That's why sometimes you need a human to do the thresholding at a place that is reasonably good. You might have some false blobs, but then perhaps you can go and get rid of those some other way, such as by size or shape filtering.

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harjeet singh
harjeet singh el 21 de Dic. de 2015
Editada: harjeet singh el 21 de Dic. de 2015
may be this code will help you
clear all
close all
warning off
clc
img1=imread('word.png');
[m n x]=size(img1);
figure(1)
imshow(img1)
drawnow
img2=img1(:,:,1)<80;
img2=bwareaopen(img2,50);
figure(2)
imshow(img2)
[lab,num]=bwlabel(img2);
figure(1)
imshow(img1)
hold on
for i=1:num
[r,c]=find(lab==i);
plot([mean(c) mean(c)],[min(r) max(r)],'r');
text(mean(c)+5,m,num2str(max(r)-min(r)));
hold on
end
  7 comentarios
harjeet singh
harjeet singh el 23 de Dic. de 2015
yes meghashree its the pixel count
Meghashree G
Meghashree G el 23 de Dic. de 2015
oh ok sir .thanks a lot :) @image analyst ,sir thank you for you also :)

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