飞机开关门状态自动识别

目标： 利用opencv图像识别技术实现从摄像头视频中自动识别飞机门开关动作。

相关技术：OpenCV，图像识别，C++。

实现基本原理：通过识别飞机舱门上的小圆窗位置变化来判断门状态。

效果图片：

核心代码：

//检测圆窗，返回检测到的圆心坐标值
Point houghCircleDetec(Mat frame) {Mat roiImage(frame, Rect(X, Y, WIDTH, HEIGHT));Mat grayImage;cvtColor(roiImage, grayImage, CV_BGR2GRAY);vector<Vec3f> circles;//霍夫圆检测HoughCircles(grayImage, circles, CV_HOUGH_GRADIENT, 1.5, 20, 200, 75, 20, 35);//绘制出检测到的圆if (isDebug) {for (size_t i = 0; i < circles.size(); i++){Point center(cvRound(circles[i][0])+X, cvRound(circles[i][1])+Y);int radius = cvRound(circles[i][2]);circle(frame, center, radius, Scalar(155, 50, 255), 1, 8, 0);putText(frame,to_string(radius),center,FONT_HERSHEY_PLAIN,6,Scalar(255,100,40),1,8,false);}}if (circles.size() > 0) {Point center(cvRound(circles[0][0]), cvRound(circles[0][1]));return center;}else{Point temp(0, 0);return temp;}
}

/**
*滑动门状态检测
*@param values 圆心坐标值集合
*@return 门的状态值
*/
int doorStyle_centerPoint(queue<int> values)
{int firstX = values.front();int lastX = values.back();int subtractionValue = firstX - lastX;if (subtractionValue > 100)return OPEN;else if (subtractionValue < -100) {return CLOSE;}return UNKNOW;
}

/**门状态识别
*@param f 回调函数
*@param videoName 为视频文件的全名称
*@return 返回运行结果值。
*/
int DoorRecognition(callback_t f, const char* videoName)
{VideoCapture capture;capture.open(videoName);if (!capture.isOpened()){cout << "视频不能打开\n";return 0;}//	deque<int> deqCircleCenterpoints;queue<int> queueDebugData;bool isOk = false;int style = 0;for (;;){Mat frame;capture >> frame;if (frame.empty()){break;}//绘制检测的ROI矩形框边界if(isDebug)rectangle(frame, Rect(X, Y, WIDTH, HEIGHT), Scalar(255, 0, 255));if (!isOk) {//进行霍夫圆检测Point centerPoint = houghCircleDetec(frame);if (centerPoint.x == 0 && centerPoint.y == 0) {//没有检测到圆//进行圆形拱形检测}else {//检测到圆queueDebugData.push(centerPoint.x);int doorStyle = doorStyle_centerPoint(queueDebugData);if (doorStyle > 0)isOk = true;/*deqCircleCenterpoints.push_back(centerPoint.x);if (deqCircleCenterpoints.size() > 40){deqCircleCenterpoints.pop_front();}*/}}if (isOk) {f(style);//break;}imshow("frame", frame);if (waitKey(30) >= 0) break;}//显示圆心数据序列内容if (isDebug){int pointNum = queueDebugData.size();for (size_t i = 0; i < pointNum; i++){double temp= queueDebugData.front();cout << temp<< endl;queueDebugData.pop();}}waitKey(0);capture.release();return 1;
}

实现缺陷：图片识别之前没有经过滤波处理，判断条件过于单一，容易误判等。