MATLAB: How to crop images and save it to matrix after vision.For​egroundDet​ector

computer visioncropimage analysisimage processingvideo processing

Hello. Vision.ForegroundDetector is so amazing!
Could you let me know how to get several images inbox as a matrix?
I want to save these images as matrix.
I want to use several images like this. How can I crop this like image?
I am using this code.
videoSource = VideoReader('shahar_run.avi');
detector = vision.ForegroundDetector(...
       'NumTrainingFrames', 5, ...
       'InitialVariance', 30*30);
blob = vision.BlobAnalysis(...
       'CentroidOutputPort', false, 'AreaOutputPort', false, ...
       'BoundingBoxOutputPort', true, ...
       'MinimumBlobAreaSource', 'Property', 'MinimumBlobArea', 250);
shapeInserter = vision.ShapeInserter('BorderColor','White');
videoPlayer = vision.VideoPlayer();
while hasFrame(videoSource)
     frame  = readFrame(videoSource);
     fgMask = detector(frame);
     bbox   = blob(fgMask);
     out    = shapeInserter(fgMask,bbox);
     videoPlayer(out);
     pause(0.1);
end

Best Answer

Check the following code
videoSource = VideoReader('denis_wave2.avi');
detector = vision.ForegroundDetector(...
    'NumTrainingFrames', 5, ...
    'InitialVariance', 30*30);
blob = vision.BlobAnalysis(...
    'CentroidOutputPort', false, 'AreaOutputPort', false, ...
    'BoundingBoxOutputPort', true, ...
    'MinimumBlobAreaSource', 'Property', 'MinimumBlobArea', 50);
shapeInserter = vision.ShapeInserter('BorderColor','White');
videoPlayer = vision.VideoPlayer();
bounding_boxes = {};
while hasFrame(videoSource)
    frame  = readFrame(videoSource);
    fgMask = detector(frame);
    bbox   = blob(fgMask);
    for i=1:size(bbox, 1)
        x = bbox(i, :);
        bounding_boxes{end+1} = fgMask(x(2):sum(x([2 4])), x(1):sum(x([1 3])));
    end
    out    = shapeInserter(fgMask,bbox);
    videoPlayer(out);
    pause(0.1);
end
The bounding_boxes is a cell array and its each element is a cropped image. You can check the output as
imshow(bounding_boxes{1})
imshow(bounding_boxes{2})
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