You could use the new "machine vision" toolbox which is specially built for vision applications. See code below:
vid = videoinput('winvideo', 1, 'RGB24_320x240'); %select input device
hvpc = vision.VideoPlayer; %create video player object
src = getselectedsource(vid);
vid.FramesPerTrigger =1;
vid.TriggerRepeat = Inf;
vid.ReturnedColorspace = 'rgb';
src.FrameRate = '30';
start(vid)
%start main loop for image acquisition
for t=1:500
imgO=getdata(vid,1,'uint8'); %get image from camera
hvpc.step(imgO); %see current image in player
end
As you can see, you can acquire the image with getdata. The bottleneck in video applications in Matlab was the preview window, which delayed to code substantially. The new vision.VideoPlayer is a lot faster (i have used this code in real time vision applications in Matlab. When i had written the first version without the vision toolbox, achieving frame rates at about 18 fps and using the new toolbox got to around 70!).
Note: I you need speed in image apps using Matlab, you should really consider using OpenCV libs through mex to get a decent performance in image manipulation.
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