Documentation

Cameras

Image Acquisition Toolbox™ enables you to acquire images and video from cameras and frame grabbers directly into MATLAB® and Simulink®. Using the Image Acquisition Toolbox Support Package for GigE Vision^® Hardware or the MATLAB^® Support Package for USB Webcams, set up a camera to acquire the real-time images to perform the analysis.

For more information on setting up the camera, see Device Connection (Image Acquisition Toolbox).

Target

Use the following commands to create a target to print for use in the exercise. The code generates a postscript file that can be opened and printed double-sided, with the target on one side, and the checkerboard for camera calibration on the other side.

distance = 10; % meters
offset_mm = 0; % mm
print_target = true;
LaserTargetExample.make_target_airpistol10m(distance, ...
offset_mm, print_target)

You can find pre-made targets in the +LaserTargetExample/targets_for_printing folder.

Setup

Set up the camera so that it faces the checkerboard side of the target. The shooter faces the target. You can keep the target and camera in fixed positions by mounting them on a board.

Calibrating the Image

Camera calibration is the process of estimating the parameters of the lens and the image sensor. These parameters measure objects captured by the camera. Use the Camera Calibrator (Computer Vision Toolbox) app to detect the checkerboard pattern on the back of the target, and remove any distortion. Determine the threshold of ambient light on the target. You may need to adjust camera settings or the lighting so that the image is not saturated. Use the pointsToWorld function to determine world coordinates of the image points.

For more information, see What Is Camera Calibration? (Computer Vision Toolbox).

Finding and Scoring the Shot

The algorithm scores the shots by detecting the bright light of the laser pistol. While shooting, get a frame and detect if there is a bright spot. If there is a bright spot over the specified threshold, process that frame.

Use blob analysis to find the center of the bright spot, and translate the location from pixel coordinates to world coordinates. The blob analysis is done in fixed point because the image is stored as an 8-bit signed integer. After finding the center of the bright spot in world coordinates, calculate its distance from the bullseye at the origin and assign a point value to the shot.

Shot Database

Each time you shoot, the hits are recorded in a file named ShotDatabase.csv. You can load the data into a table object using readtable to visualize it. For example, after shooting, which populates the ShotDatabase.csv file, the following code plots the center of a group of many shots.

T = readtable('ShotDatabase.csv');
LaserTargetExample.make_target_airpistol10m;
LaserTargetExample.plot_shot_points(T.X, T.Y);
ax = gca;
line(mean(T.X)*[1,1], ax.YLim);
line(ax.XLim, mean(T.Y)*[1,1]);
grid on;

Simulation Recordings

Each time you shoot, the video frames in which shots were detected are stored in files in a folder named simulation_recordings. You can load these files and explore the raw data from the shots. You can also edit the algorithm.

The variable frames contains the first frame which was used for calibration, plus ten frames for each detected shot. The first frame in each run of ten is where a shot was detected. You can see your hand movement in the subsequent frames. You can make a short animation of the data using the following code.

d = dir(fullfile('simulation_recordings','*.mat'));
record = load(fullfile(d(1).folder, d(1).name));
t = LaserTargetExample.SerialDateNumber_to_seconds(...
    record.times);
t = t-t(1);
figure
for k = 1:size(record.frames, 3)
    imshow(record.frames(:,:,k), ...
        'InitialMagnification','fit');
    title(sprintf('Time since beginning of round: %.3f seconds',...
        t(k)))
    drawnow
end