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bwareaopen will then treat bw as a sequence of two-dimensional images rather than one three-dimensional image.įinally, we label each individual object (using bwlabel) and compute its corresponding center of mass (using regionprops). The third argument, 8, tells bwareaopen to assume that pixels are connected only to their immediate 8 neighbors in each frame. Removes all objects containing fewer than 20 pixels. The technique we’ll use, area opening, removes objects in a binary image that are too small. The frame shows a ball, attached by a string to the ceiling, swinging over the state of Alabama.Īs you can see, the resulting binary image has a small extra spot that should be removed. We display the tenth frame using the Image Processing Toolbox function imview. The vector t contains the time stamps for each frame. It represents an image sequence with 288 rows, 352 columns, 3 color components, and 50 frames. Variable f is a four-dimensional array of size 288-by-352-by-3-by-50. The getdata function transfers the acquired images into the MATLAB workspace. The processing does not need to start before the acquisition is done, so we’ll use the wait function to wait for the acquisition to stop.
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Since acquisition occurs in the background, the MATLAB command line is free and we can start processing images in the background. Set(getselectedsource(vid), 'FrameRate', 3)īy default, acquisition begins immediately.
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Next, we specify that we want to acquire 50 frames at 3 frames per second. (Use imaqhwinfo to determine your device’s identifier number and supported video formats.) First, we connect to a Windows video device using the videoinput function.
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