Each image is composed of an array of M*N pixels (contraction of “picture element”) with M rows and N columns of pixels. Each pixel contains a certain value for red, green and blue. Varying these values for red, green, blue (RGB) we can get almost any color.

Figure 1

Image Storage in Matlab

The RGB format is a practical method to represent color images. Matlab creates three matrices (or three M x N arrays) with each matrix representing normalized components of red, green or blue to read and store each of the frames of the video. Any pixel’s color is determined by the combination of Red, Green and Blue values stored in the three matrices at that pixel’s location. This is how Matlab reads and manipulates .jpg files.

Images:

picture (row, column, rgb value)

For example, picture (12, 78, 1) corresponds to the red component of the pixel at row 12 and column 78; picture(12, 78, 2) corresponds to the green component of the pixel and picture(12, 78, 3) gives us the blue component of the pixel at that location.

Videos:

frames(row, column, rgb value, frame)

Videos have an extra dimension for the frame number. So frames(12,78,1,5) would correspond to the red component of the pixel in the 12th row and 78th column of the 5th frame. To get the entire frame, we could just say frames(:,:,:,5).

When this statement is encountered, the program retrieves all the frames acquired at the last trigger and then empties the buffer.

This function allows us to “peek” at the last M frames collected by the camera. The frames are copied, but not cleared, from the camera’s buffer into Matlab’s workspace.

Both functions take about the same amount of time to run. Interestingly, the number of frames acquired at a time does not affect the execution time much. It takes about as long to acquire 1 frame as it does to acquire 50. Therefore, to make the program more efficient, we should collect large chunks of data at a time.

To make sure that we don’t miss any of the action while the user is waving the drumsticks around in front of the camera, we should also make sure that we can get all the frames from when the program starts running till the user turns of the LEDs. Due to memory limitations, our computer could collect maximum of 240 frames, or about 8 seconds of the video, which is clearly not enough. It is unlikely that your computer could do much better.