OpenCV 帧差法

目标检测中最简单的方法是利用减除背景的方式，先采集一张背景图像，然后在目标检测的过程中减去之前的背景得到目标物体，这种方法容易受到光照、摄像机位置等因素的影响，效果并不理想。

这里采用帧差法（frame differencing），利用前后帧画面的差别取得新出现的物体。

过程如下：

diff1 = |nextFrame - curFrame|

diff2 = |curFrame - preFrame|

output = |diff1 and diff2|

最后一步采用and操作能使得结果中噪声影响较小，效果更稳定。

代码如下：

void main()
{
	Mat frame;
	Mat preFrame, nextFrame, frame1, frame2, output;
	VideoCapture cap(0);

	if (!cap.isOpened())
	{
		cout << "error" << endl;
		waitKey(0);
		return;
	}

	cap >> preFrame;
	cap >> frame;
	cvtColor(preFrame, preFrame, CV_BGR2GRAY);
	cvtColor(frame, frame, CV_BGR2GRAY);
	namedWindow("res");

	namedWindow("show");
	imshow("show", frame);
	while (true)
	{
		// Capture the current frame
		cap >> nextFrame;
		cvtColor(nextFrame, nextFrame, CV_BGR2GRAY);
		imshow("show", frame);
		absdiff(nextFrame, frame, frame1);
		absdiff(frame, preFrame, frame2);
		bitwise_and(frame1, frame2, output);
		output = frameDiff(preFrame, frame, nextFrame);
		imshow("res", output);
		if (waitKey(30) >= 0)break;
		preFrame = frame;
		frame = nextFrame;
	}

	cap.release();
	// Close all windows
	destroyAllWindows();
}

Mat frameDiff(Mat prevFrame, Mat curFrame, Mat nextFrame)
{
	Mat diffFrames1, diffFrames2, output;
	// Compute absolute difference between current frame and the nextframe
	absdiff(nextFrame, curFrame, diffFrames1);
	// Compute absolute difference between current frame and the previous frame
	absdiff(curFrame, prevFrame, diffFrames2);
	// Bitwise "AnD" operation between the above two diff images
	bitwise_and(diffFrames1, diffFrames2, output);
	return output;
}

效果图如下：