W4算法基于背景建模的运动目标检测

痛定思痛。 2023-01-16 09:52 169阅读 0赞

W4算法对每个像素点统计三个特征值：最小灰度值、最大灰度值以及最大帧间差分值。所有像素点的特征值就构成了背景模型，比较当前帧与背景模型就能检测出运动的目标。具体步骤可分为三部分：**模型初始化、目标检测以及模型更新。**

**模型初始化**：首先遍历初始数帧，并对每个像素点计算灰度中值和标准差，然后计算每个像素点帧间灰度变化的最大值、最小值以及最大帧间差分值。计算时间过长，没有进行优化。

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**目标检测：**

**![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dlaXhpbl80NTY0NTI4MQ_size_16_color_FFFFFF_t_70 1][]**

#include <iostream>
    #include<opencv2/opencv.hpp>
    #include <vector>
    using namespace cv;
    using namespace std;
    
    //每个像素的灰度中值
    bool comp(int x, int y)
    {
    	return x > y;
    }
    void sort_vector(vector <int> v)
    {
    	
    	sort(v.begin(), v.end(), comp);
    }
    
    //每个像素的灰度值标准差
    double mean(vector <int> v) {
    	double ans = 0.0;
    	for (int i = 0; i < v.size(); i++) {
    		ans += v[i];
    	}
    	ans = ans / v.size();
    	return ans;
    }
    
    double vector_stddev(vector <int> v) {
    	double a1 = mean(v);
    	double a2 = 0.0;
    	for (int i = 0; i < v.size(); i++) {
    		a2 = (a1 - v[i]) * (a1 - v[i]);
    	}
    	a2 = sqrt(a2 / v.size());
    	return a2;
    }
    
    //相邻帧像素灰度差分值
    int vector_diff(vector <int> v) {
    	vector<int> temp;
    	for (int i = 0; i < v.size()-1; i++) {
    		int result = abs(v[i + 1] - v[i]);
    		temp.push_back(result);
    	}
    	int max = *max_element(temp.begin(), temp.end()); ;
    	return max;
    }
    
    //相邻帧像素灰度差分值的平均值
    double mean_diff(vector <int> v) {
    	vector<int> temp;
    	for (int i = 0; i < v.size() - 1; i++) {
    		int result = abs(v[i + 1] - v[i]);
    		temp.push_back(result);
    	}
    	double a1 = mean(temp);
    	return a1;
    }
    
    
    
    int main()
    {
    	VideoCapture capture;
    	Mat frame,framegray,result;
    	//保存目标轨迹  
    	std::vector<Point> pt;
    	//capture.open(0);
    	frame = capture.open("D:/testimage/video/fish.mp4");	//F:/opencv/sources/amples/data/vtest.avi  D:/testimage/CXK.avi D:/testimage/video/fish.mp4
    	if (!capture.isOpened())
    	{
    		printf("can not open camera \n");
    		return -1;
    	}
    
    	int iVideoTime = capture.get(CAP_PROP_FRAME_COUNT); // capture.get(CAP_PROP_FPS);
    	int Frame_start= capture.get(CAP_PROP_POS_FRAMES);
    	capture.read(frame);
    	
    	vector <double> all_diff;
    	cvtColor(frame, result, COLOR_RGB2GRAY);
    	//namedWindow("input", WINDOW_AUTOSIZE);
    	for (int i = 0; i < frame.rows; i++)
    	{
    		vector <int> v_median;
    		for (int j = 0; j < frame.cols; j++)
    		{
    			//temp1.push_back(gray_value);
    			while (capture.read(frame) && Frame_start < 20)
    			{
    				cvtColor(frame, framegray, COLOR_RGB2GRAY);
    				int gray_value = framegray.at<uchar>(i, j);
    				//cout << gray_value << endl;
    				v_median.push_back(gray_value);
    				Frame_start++;
    				//imshow("input", frame);
    				//waitKey(10);
    			}
    
    			/*判断当前像素与灰度中值差值的绝对值是否小于2倍标准差*/
    			
    			double temp = vector_stddev(v_median);
    			double error = abs(framegray.at<uchar>(i, j) - v_median[v_median.size() / 2.0]) - 2 * temp;
    			if (error < 0) {
    			
    				int diff = vector_diff(v_median);
    				double Mean_diff = mean_diff(v_median);
    				cout << "d(x)相邻帧像素差分值：" << diff << endl;
    				cout << "d(x)相邻帧像素差分值的平均值：" << Mean_diff << endl;
    				sort_vector(v_median);
    
    				cout << "m(x)最大值：" << v_median[0] << endl;
    				cout << "n(x)最小值：" << v_median[v_median.size() - 1] << endl;
    
    				cout << "坐标（" << i << "，" << j << "）的灰度中值：" << v_median[v_median.size() / 2.0] << endl;
    				cout << "坐标（" << i << "，" << j << "）的灰度标准差：" << temp << endl;
    				cout << "error：" << error << endl;
    				int gray_value = framegray.at<uchar>(i, j);
    
    				if (abs(gray_value - v_median[0]) < 2 * Mean_diff || abs(gray_value - v_median[v_median.size() - 1]) < 2 * Mean_diff) {
    
    					result.at<uchar>(i, j) = 0;
    				}
    				else
    				{
    					result.at<uchar>(i, j) = 255;
    				}
    				
    			}
    
    			
    			Frame_start = 0;
    			frame = capture.open("D:/testimage/video/fish.mp4");
    			cvtColor(frame, framegray, COLOR_RGB2GRAY);
    		}
    		cout << "--------"<< i <<"---------" << endl;
    		Frame_start = 0;
    		frame = capture.open("D:/testimage/video/fish.mp4");
    		cvtColor(frame, framegray, COLOR_RGB2GRAY);
    	}
    	namedWindow("result", WINDOW_AUTOSIZE);
    	imshow("result", result);
    	capture.release();
    	system("pause");
    	return 0;
    
    }

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