基于opencv的影像亮度例外檢測

影像亮度例外檢測主要就是求一張圖片的平均亮度，如果大于閾值則判斷為過亮，小于閾值則判斷為過暗，實際使用時可能不是對整張圖片進行檢測，而是只檢測圖片的某個區域，這時候可以根據傳入的坐標對特定區域進行檢測，

另外下面的代碼中是驗證了幾種方法，最終用的就是平均值的方法，也就是代碼中的da，

/***************************************************************************
Description:根據傳入的信號燈結構體，求出左上角和右下角的坐標
parameter:
    lightStr:影像中包含的信號燈坐標；
	lightNum:信號燈框的數量，
    minNum:左上角點在陣列中的下標，
    maxNum:右下角點在陣列中的下標
return：
    0：success；
    1：fail
***************************************************************************/
int minAndMax(tlight::LightClock *lightStr, unsigned int lightNum, int &minNum, int &maxNum)
{
    
    int xmin = lightStr[0].xmin;
	int xmax = lightStr[0].xmax;
	
    //求出左上角點在陣列中的下標
    for(int i = 0; i < lightNum; i++)
    {
         if(lightStr[i].xmin < xmin )
         {
             printf("i=%d,lightStr[i].xmin:%d,xmin:%d\n", i, lightStr[i].xmin, xmin);
             xmin = lightStr[i].xmin;
			 minNum = i;
         }
    }
 
    //求出右下角點在陣列中的下標
	for(int i = 0; i < lightNum; i++)
    {
         if(lightStr[i].xmax > xmax )
         {
             printf("i=%d,lightStr[i].xmax:%d, xmax:%d\n", i, lightStr[i].xmax, xmax);
             xmax = lightStr[i].xmax;
			 maxNum = i;
         }
    }
 
	return 1;
 
 
}
 
 
 
/*****************************************************************************
Description:判斷影像是否逆光，過亮；
parameter:
    inputImage：要檢測的輸入影像；
	lightStr:影像中包含的信號燈坐標；
	lightNum:信號燈框的數量，
return:
    21：影像過亮
    22：影像過暗
	20：影像正常
******************************************************************************/
int isBackLight(IplImage *inputImage, tlight::LightClock *lightStr, uint32_t lightNum)
{
    float da = 0.0;
	float cast = 0.0;
	float Ma = 0.0;
 
    int xmin = 0;
	int ymin = 0;
	int xmax = 0;
	int ymax = 0;
    int minNum = 0;
	int maxNum = 0;
	
    //首先把IplImage轉化為Mat格式，并且轉換為灰度圖，
    cv::Mat inputMat = cv::cvarrToMat(inputImage);
	printf("inputMat.rows:%d\n", inputMat.rows);
	printf("inputMat.cols:%d\n", inputMat.cols);
 
	for(int i  = 0; i < lightNum;i++)//除錯，記得洗掉
	{
	    printf("lightStr[%d].xmin:%d;\n", i, lightStr[i].xmin);
		printf("lightStr[%d].ymin:%d;\n", i, lightStr[i].ymin);
		printf("lightStr[%d].xmax:%d;\n", i, lightStr[i].xmax);
		printf("lightStr[%d].ymax:%d;\n", i, lightStr[i].ymax);
	}
 
	cv::Mat inputRec;
 
    if(0 == lightNum)//沒有框的坐標，只檢測上半部分
    {
        inputRec = inputMat(cv::Rect(0, 0, inputMat.cols, (inputMat.rows)/2 ));
     	printf("inputRec.rows:%d\n", inputRec.rows);
	    printf("inputRec.cols:%d\n", inputRec.cols);
        
    }
	else//有坐標資訊的，按照坐標進行檢測，
	{
        //找出xmin的最小值，和xmax的最大值，這兩個點對應的就是相應的左上角和右下角，
        minAndMax(lightStr, lightNum, minNum, maxNum);
	    xmin = lightStr[minNum].xmin;
		ymin = lightStr[minNum].ymin;
		xmax = lightStr[maxNum].xmax;
		ymax = lightStr[maxNum].ymax;
        printf("lightNum:%d, minNum:%d, maxNum:%d\n", lightNum, minNum, maxNum);
		printf("xmin:%d, ymin:%d,xmax:%d,ymax:%d\n", xmin, ymin, xmax, ymax);
		//然后把矩形框外擴.
		xmin = ((xmin - 100) < 0) ? 0: (xmin - 100);
		ymin = ((ymin - 20) < 0) ? 0: (ymin - 20);
		xmax = ((xmax + 100) > inputMat.cols)? inputMat.cols : (xmax + 100);
		ymax = ((ymax + 300) > inputMat.rows)? inputMat.rows : (ymax + 300);
 
		printf("xmin:%d, ymin:%d,xmax:%d,ymax:%d\n", xmin, ymin, xmax, ymax);
 
		inputRec = inputMat(cv::Rect(xmin, ymin, (xmax - xmin), (ymax - ymin)));
		//printf("");
		
	}
 
	
	//cv::rectangle(inputMat, cvPoint(722, 28), cvPoint(813, 67), cvScalar(255, 0, 0), 2, 1, 0);//除錯，記得洗掉
	//cv::imwrite("./test.jpg", inputMat);//除錯，記得洗掉
	
	cv::Mat GRAYimg;
	cv::cvtColor(inputRec, GRAYimg, CV_BGR2GRAY);
	
	float a = 0;
	int Hist[256];
	for (int i = 0; i < 256; i++)
	{
		Hist[i] = 0;
	}
 
	float ave = 0.0;
	long sum = 0.0;
	for (int i = 0; i < GRAYimg.rows; i++)
	{
		for (int j = 0; j < GRAYimg.cols; j++)
		{
			//printf("GRAYimg.at<uchar>(i, j):%d\n", GRAYimg.at<uchar>(i, j));
			sum += GRAYimg.at<uchar>(i, j);
 
		}
	}
	printf("function:%s,sum:%d\n", __FUNCTION__, sum);
	ave = sum / (GRAYimg.rows * GRAYimg.cols);
	//printf("ave:%f\n", ave);
 
	int para = ave;
	int aveHigh = 0;
	for (int i = 0; i < GRAYimg.rows; i++)
	{
		for (int j = 0; j < GRAYimg.cols; j++)
		{
			a += float(GRAYimg.at<uchar>(i, j));
			//a += float(GRAYimg.at<uchar>(i, j) - para);
			//a += float(GRAYimg.at<uchar>(i, j) - ave);
			int x = GRAYimg.at<uchar>(i, j);
			if (x > ave)
			{
				aveHigh++;
				Hist[x]++;
			}
		}
	}
	da = a / float(GRAYimg.rows * GRAYimg.cols);//da是平均值
	printf("function:%s,da:%f\n", __FUNCTION__, da);
	float D = abs(da);
	//float Ma = 0;
	for (int i = 0; i < 256; i++)
	{
		if (i > ave)
		{
			Ma += abs(i - ave) * Hist[i];
		}
		//Ma += abs(i - para - da) * Hist[i];
		//Ma += abs(i - ave - da) * Hist[i];
	}
	Ma /= float(aveHigh);
	//Ma /= float((GRAYimg.rows * GRAYimg.cols));
	float M = abs(Ma);
	float K = D / M;
	cast = K;
 
	//除錯，記得洗掉
	char debugName[20] = {};
 
 
	//if(da > 210.00)//過亮
	if(da > lightThresh)
	{
	    sprintf(debugName, "./%f.jpg", da);
	    //cv::imwrite(debugName, inputMat);//除錯，記得洗掉，
	    return 21;
	}
	//else if(da < 25.00)
	else if(da < darkThresh)
	{
	    //printf("++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ guoan+++++\n");
	    return 22;
	}
	else//正常
	{  
	    //printf("--------------------------------------------------------------------------------------liang-du-zheng-chang\n");
	    //cv::imwrite(debugName, inputMat);
	    return 20;
	}
}

專案中實際使用時可以把lightThresh寫到組態檔中，上電初始化時讀取組態檔，