foregroundDetector = vision.ForegroundDetector('NumGaussians', 3, ...
'NumTrainingFrames',80 );
videoReader = vision.VideoFileReader('visiontraffic.avi');
for i = 1:150
frame = step(videoReader);
foreground = step(foregroundDetector, frame);
end
figure; imshow(frame); title('Video Frame');
figure; imshow(foreground); title('Foreground');
se = strel('square', 3);
filteredForeground = imopen(foreground, se);
figure; imshow(filteredForeground); title('Clean Foreground');
blobAnalysis = vision.BlobAnalysis('BoundingBoxOutputPort', true, ...
'AreaOutputPort', false, 'CentroidOutputPort', false, ...
'MinimumBlobArea', 150);
bbox = step(blobAnalysis, filteredForeground);
result = insertShape(frame, 'Rectangle', bbox, 'Color', 'green');
numCars = size(bbox, 1);
result = insertText(result, [10 10], numCars, 'BoxOpacity', 1, ...
'FontSize', 14);
figure; imshow(result); title('Detected Cars');
videoPlayer = vision.VideoPlayer('Name', 'Detected Cars');
videoPlayer.Position(3:4) = [650,400];
se = strel('square', 3);
while ~isDone(videoReader)
frame = step(videoReader);
foreground = step(foregroundDetector, frame);
filteredForeground = imopen(foreground, se);
bbox = step(blobAnalysis, filteredForeground);
result = insertShape(frame, 'Rectangle', bbox, 'Color', 'green');
numCars = size(bbox, 1);
result = insertText(result, [10 10], numCars, 'BoxOpacity', 1, ...
'FontSize', 14);
step(videoPlayer, result);
end
release(videoReader);