/*
* processFrame
*
* creates a threshold image of frame, splits the thresholded image into left and
* right halves and then tracks for the configured color in each half, setting the
* left and right paddle positions accordingly
*
* preconditions: frame must be a valid Mat object representing a single frame from
* from a VideoCapture object
* postconditions: sets left and right paddles according to color detected in the
* left and right halves of the frame, respectively
*/
void ColorPaddleDetector::processFrame(Mat &frame)
{
flip(frame, frame, 1);
Mat thres;
createThresholdImg(frame, thres);
// create left and right threshold images for seperate color detection in
// left and right sides of the frame
int x = thres.cols / 2;
int y = thres.rows;
Mat thresholdLeft(thres, Rect(0, 0, 320, 480));
Mat thresholdRight(thres, Rect(320, 0, 320, 480));
// detect motion in the left and right frames
detectMotion(thresholdLeft, frame, IS_RED);
detectMotion(thresholdRight, frame, IS_BLUE);
}
/*
* processFrame
*
* uses sequential images to detect motion in the left and right halves of the frame.
*
* preconditions: frame must be a valid Mat object representing a single frame from
* from a VideoCapture object
* postconditions: sets left and right paddles according to motion detected in the
* left and right halves of the frame, respectively
*/
void MotionPaddleDetector::processFrame(Mat& frame) {
Mat frame2, gray, gray2, thres, diff;
// use sequential images (frame and frame2) for motion detection
// read in frame and convert to grayscale
m_vid->read(frame);
flip(frame, frame, 1);
cvtColor(frame, gray, COLOR_BGR2GRAY);
// read in frame2 and convert to grayscale
m_vid->read(frame2);
flip(frame2, frame2, 1);
cvtColor(frame2, gray2, COLOR_BGR2GRAY);
// create difference image of frame1 and frame2 after being converted to
// grayscale images
absdiff(gray, gray2, diff);
// threshold difference
threshold(diff, thres, THRESHOLD_SENSITIVITY, 255, THRESH_BINARY);
// blur the image. output will be an intensity image
blur(thres, thres, cv::Size(BLUR_SIZE, BLUR_SIZE));
// threshold intensity image to get binary image (after blurring)
threshold(thres, thres, THRESHOLD_SENSITIVITY, 255, THRESH_BINARY);
// split threshold (now binary image) into left and right halves
int x = thres.cols / 2;
int y = thres.rows;
Mat thresholdLeft(thres, Rect(0, 0, x, y));
Mat thresholdRight(thres, Rect(x, 0, x, y));
// detect motion in each half of the binary image
detectMotion(thresholdLeft, frame, IS_RED);
detectMotion(thresholdRight, frame, IS_BLUE);
}
