如何在matlab中检测瞳孔？ [关闭]

Question

下面是我从某处下载的源代码，它能够检测红色物体并显示其中心坐标。

a = imaqhwinfo;
[camera_name, camera_id, format] = getCameraInfo(a);


% Capture the video frames using the videoinput function
% You have to replace the resolution & your installed adaptor name.
vid = videoinput(camera_name, camera_id, format);

% Set the properties of the video object
set(vid, 'FramesPerTrigger', Inf);
set(vid, 'ReturnedColorspace', 'rgb')
vid.FrameGrabInterval = 1;

%start the video aquisition here
start(vid)

% Set a loop that stop after 100 frames of aquisition
while(vid.FramesAcquired<=100)

% Get the snapshot of the current frame
data = getsnapshot(vid);

% Now to track red objects in real time
% we have to subtract the red component 
% from the grayscale image to extract the red components in the image.
diff_im = imsubtract(data(:,:,1), rgb2gray(data));
%Use a median filter to filter out noise
diff_im = medfilt2(diff_im, [3 3]);
% Convert the resulting grayscale image into a binary image.
diff_im = im2bw(diff_im,0.17);

% Remove all those pixels less than 300px
diff_im = bwareaopen(diff_im,300);

% Label all the connected components in the image.
bw = bwlabel(diff_im, 8);

% Here we do the image blob analysis.
% We get a set of properties for each labeled region.
stats = regionprops(bw, 'BoundingBox', 'Centroid');

% Display the image
imshow(data)

hold on

%This is a loop to bound the red objects in a rectangular box.
for object = 1:length(stats)
    bb = stats(object).BoundingBox;
    bc = stats(object).Centroid;
    rectangle('Position',bb,'EdgeColor','r','LineWidth',2)
    plot(bc(1),bc(2), '-m+')
    a=text(bc(1)+15,bc(2), strcat('X: ', num2str(round(bc(1))), 'Y: ',  num2str(round(bc(2)))));
    %disp(' X-Coordinate   Y-cordinate')
    %x=gallery('uniformdata',[5 3],0);
    %disp(x)
    set(a, 'FontName', 'Arial', 'FontWeight', 'bold', 'FontSize', 12, 'Color',      'yellow');
end

hold off
end
% Both the loops end here.

% Stop the video aquisition.
stop(vid);

% Flush all the image data stored in the memory buffer.
flushdata(vid);

% Clear all variables
% clear all
sprintf('%s','That was all about Image tracking, Guess that was pretty easy :) ')

问题是我想检测眼睛的瞳孔，所以我需要检测图像中的黑色，但我不知道如何修改代码以使其能够检测黑色。那么，对此有什么想法吗？请帮助我，谢谢大家。

Answer 1

diff_im = imsubtract(data(:,:,1), rgb2gray(data));

是算法提取颜色数据的红色分量的地方。 所以这就是你必须做出一些改变的地方。

您可以继续使用灰度，而不是提取红色分量（如代码的 cmets 中所指出的那样）。

diff_im = rgb2gray(data);

但我认为这会导致找到白色物体。为了解决这个问题，您可以更改 blob 分析，或者只是反转输入。我认为它是这样的：

diff_im = imcomplement(rgb2gray(data));

但我无法在此处对其进行测试，因为我无法访问图像处理工具箱。你可以自己测试一下吗？

使用image package 以八度音阶进行测试

我用来测试的图片找到here。

% Get the snapshot of the current frame
  data = imread('child-eye1-560x372.jpg');

% Now to track red objects in real time we have to subtract the red component
% from the grayscale image to extract the red components in the image.
  diff_im = rgb2gray(data);
  imwrite(diff_im,'diff_im.jpg');
%Use a median filter to filter out noise
  diff_im = medfilt2(diff_im, [3 3]);
  imwrite(diff_im,'diff_im_filt1.jpg');
% Convert the resulting grayscale image into a binary image.
  diff_im = im2bw(diff_im,0.17);
  imwrite(diff_im,'diff_im_filt2.jpg');

这些只是过滤步骤，blob 分析功能在 octave 中不可用。生成的图像是：

如果我将im2bw的过滤器值降低到0.07，结果会更好：

如您所见，这部分过程似乎没问题。最后一张图片是二进制的，所以大的大斑点不应该太难找到。和以前一样，我自己无法测试...

也许问题不在于算法，而在于您提供的数据。如果图片中有很多小黑点，算法会找到它们并将它们包含在结果中..