OPENCV手势动作识别-石头剪刀布

作为一个OpenCV初学者，为了锻炼能力，决定自己写个手势识别程序，结果比网上找的程序效果还好一些，所以分享出来~~

为了得到更好的效果，我利用了背景减法。取摄像头的第一帧为背景，后面所有帧减去第一帧，这样大量减去了杂质。

比较方法用的matchShapes()函数，这个在之前博客里有介绍，这里就不说了。可以参考https://blog.csdn.net/wangshuai610/article/details/79913600点击打开链接

利用matchShapes()函数得到的返回值，去做判断。

对所有图像做相同处理，二值化处理---->中值滤波--->腐蚀--->膨胀--->查找轮廓，接着把每一帧图像与模板图像用matchShapes()函数进行匹配。最后判断出来结果。完整代码下载链接https://download.csdn.net/my点击打开链接

<textarea readonly="readonly" name="code" class="c++"> void main()
{	 
    VideoCapture cap(0);
    if(!cap.isOpened()) //检查打开是否成功
         return;
    Mat frame;
	Mat background;
	Mat dst;
	int count=0;
    while(1)
    {
        cap>>frame;
        if(!frame.empty())
        {
			count++;
			if(count==1)
				background = frame.clone(); //提取第一帧为背景帧
            //imshow("video", frame);
			dst = MoveDetect(background, frame);
			imshow("result", dst);
		</textarea>

<textarea readonly="readonly" name="code" class="c++">  //对三个模板进行处理
	Mat cloth= imread("cloth.bmp");
	cvtColor(cloth, cloth, CV_BGR2GRAY);
	threshold(cloth, cloth, 40, 255, CV_THRESH_BINARY); 
	vector<vector<Point>> contours1;
	vector<Vec4i> hierarcy1;	
	findContours(cloth, contours1, hierarcy1, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);</textarea>

<textarea readonly="readonly" name="code" class="c++"> 
threshold(diff, diff, 70, 255, CV_THRESH_BINARY);
	//imshow("threshold", diff);
 
	Mat element = getStructuringElement(MORPH_RECT, Size(3, 3));
	Mat element2 = getStructuringElement(MORPH_RECT, Size(10,10));

	medianBlur(diff, diff, 5);//滤波参数根据自己环境调整
	//imshow("medianBlur", diff);

	/*blur(diff, diff, Size(10, 10));
	imshow("blur", diff);*/

	erode(diff, diff, element);
	//imshow("erode", diff);
 
	dilate(diff, diff, element2);//膨胀参数根据自己环境调整
	imshow("dilate", diff);
	
	vector<vector<Point>> contours;  
	vector<Vec4i> hierarcy;
	findContours(diff, contours, hierarcy, CV_RETR_EXTERNAL, CHAIN_APPROX_NONE); //查找轮廓
	
	//drawContours(result, contours, -1, Scalar(0,0,255), 2, 8);  //绘制轮廓

  
	for(int i=0;i<contours.size();i++)//与三个模板分别比较匹配度
	{
		double matchrate1=matchShapes(contours1[0],contours[i],CV_CONTOURS_MATCH_I1, 0.0);
		cout<<"index1="<<i<<"---"<<setiosflags(ios::fixed)<<matchrate1<<endl;
		double matchrate2=matchShapes(contours2[0],contours[i],CV_CONTOURS_MATCH_I1, 0.0);
		cout<<"index2="<<i<<"---"<<setiosflags(ios::fixed)<<matchrate2<<endl;
		double matchrate3=matchShapes(contours3[0],contours[i],CV_CONTOURS_MATCH_I1, 0.0);
		cout<<"index3="<<i<<"---"<<setiosflags(ios::fixed)<<matchrate3<<endl;
		if(matchrate1<matchrate2&&matchrate1<matchrate3)
		{
		  Mat result= imread("cloth1.jpg");
		  imshow("jieguo", result);  
		  putText(dst, "cloth", Point(30, 70), CV_FONT_HERSHEY_COMPLEX, 2, Scalar(0, 0, 255), 2, 8);
		}
		if(matchrate2<matchrate1&&matchrate2<matchrate3)
		{
		  Mat result= imread("scissors1.jpg");
		  imshow("jieguo", result);    
		  putText(dst, "scissors", Point(30, 70), CV_FONT_HERSHEY_COMPLEX, 2, Scalar(0, 0, 255), 2, 8);
		}
		if(matchrate3<matchrate1&&matchrate3<matchrate1)
		{
		  Mat result= imread("stone1.jpg");
		  imshow("jieguo", result);  
		  putText(dst, "stone", Point(30, 70), CV_FONT_HERSHEY_COMPLEX, 2, Scalar(0, 0, 255), 2, 8);
		}
</textarea>