How can I detect that which squares are ticked in the image?

Question

AlexMT 2018-12-14

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评论： AlexMT 2018-12-16

I'm think use the normxcorr2 or imshowpair to compare the original image with ticked image, but I not sure how to do this.

Original Image:

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Answer 1

Mark Sherstan 2018-12-15

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https://ww2.mathworks.cn/matlabcentral/answers/435696-how-can-i-detect-that-which-squares-are-ticked-in-the-image#answer_352483

An almost identical question and solution can be found here

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Mark Sherstan 2018-12-15

在 MATLAB Online 中打开

Here you go :) It is a slightly different approach but basically I took the picture and located all the squares with a red box (file attachted). From there I was able to create a mask and loop through each box and check if there was something inside of it or not. Based off those results I either circled it or left it blank. Let me know if you have any questions.

A couple notes: It would be much easier if you scanned the document instead of taking a picture of it. This would also allow for the results to be repeatable as everything will have the same angles, spacing, perspective, etc... and the mask can always be treated as true. I also had to darken the image slightly as the pen marks where showing up light (may be from posting it online, switching file formats to png, etc...) but again this could easily be fixed by scanning.

clear all
close all
% Read in original and colored mask image with red squares
image = imread('image.png'); original = image;
mask = imread('mask.png');
% Create a mask and apply to image so we can focus on the boxes
BW = createMask(mask);
image(repmat(~BW,[1 1 3])) = 0;
BW2 = imbinarize(rgb2gray(image));
% Get the coordinates for each square
stats = regionprops(BW,'boundingbox','centroid');
% See if there is anything in a square
for ii = 1:numel(stats)
    tempImg = imcomplement(imcrop(BW2,stats(ii).BoundingBox));
    check = round(bwarea(tempImg));
    
    % Only put circle around boxes with something in them 
    if (check > 150)
        original = insertObjectAnnotation(original,'circle',[stats(ii).Centroid 50],'');
    end
end
% Display results
figure
imshow(original)

function [BW,maskedRGBImage] = createMask(RGB)
%createMask  Threshold RGB image using auto-generated code from colorThresholder app.
%  [BW,MASKEDRGBIMAGE] = createMask(RGB) thresholds image RGB using
%  auto-generated code from the colorThresholder app. The colorspace and
%  range for each channel of the colorspace were set within the app. The
%  segmentation mask is returned in BW, and a composite of the mask and
%  original RGB images is returned in maskedRGBImage.
% Auto-generated by colorThresholder app on 14-Dec-2018
%------------------------------------------------------
% Convert RGB image to chosen color space
I = rgb2hsv(RGB);
% Define thresholds for channel 1 based on histogram settings
channel1Min = 0.997;
channel1Max = 0.156;
% Define thresholds for channel 2 based on histogram settings
channel2Min = 0.288;
channel2Max = 1.000;
% Define thresholds for channel 3 based on histogram settings
channel3Min = 0.549;
channel3Max = 1.000;
% Create mask based on chosen histogram thresholds
sliderBW = ( (I(:,:,1) >= channel1Min) | (I(:,:,1) <= channel1Max) ) & ...
    (I(:,:,2) >= channel2Min ) & (I(:,:,2) <= channel2Max) & ...
    (I(:,:,3) >= channel3Min ) & (I(:,:,3) <= channel3Max);
BW = sliderBW;
% Initialize output masked image based on input image.
maskedRGBImage = RGB;
% Set background pixels where BW is false to zero.
maskedRGBImage(repmat(~BW,[1 1 3])) = 0;
end

Mark Sherstan 2018-12-15

One thing you could try is use a color marker instead of a pen. Use a color mask to locate a mark and then divide your image into quadrants and check that way instead of looking for specific boxes. I am sure Image Analyst will have some other good suggestions .

Image Analyst 2018-12-15

It's a little more complicated and you'll have to have labeled training images but you could use a deep learing model to find the squares. Otherwise we'll have to use fancier traditional techniques to find them. Can we guarantee that there will be 28 squares in a 7 row, 3 column format? If so, we could threshold and then find 28 blobs in a certain size range.

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Answer 2

Image Analyst 2018-12-15

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You might try the attached script. It automatically finds the boxes and inspects inside for black marks. It still needs work since the boxes are not identified by row and column, and there still needs to be some robustness about inspecting the boxes depending on how it behaves with other images. But at least it's automatically finding your boxes correctly and identifying checked boxes correctly for THIS image.