opencv中自适应阈值函数的实现（c++）

根据《面向飞机蒙皮接缝的线结构光检测技术研究_张卡》论文中的原理，编写了自适应阈值函数

原理：

 1 //计算灰度最大最小值
 2 void MaxGrayValue(Mat image,int &max,int &min)
 3 {
 4     max = 0;
 5     min = 255;
 6     Mat *im = reinterpret_cast<Mat*>((void*)&image);
 7     int height = image.rows;
 8     int width = image.cols;
 9     int N = height * width;
10     //cout << "125" << " " << "125" << " " << static_cast<int>(im->at<uchar>(Point(182, 190))) << endl;
11     for (int i = 0; i < height; i++)
12     {
13         for (int j = 0; j < width; j++)
14         {
15             if ((static_cast<int>(im->at<uchar>(Point(j, i))))>max)
16                 max = static_cast<int>(im->at<uchar>(Point(j, i)));
17             else if ((static_cast<int>(im->at<uchar>(Point(j, i))))<min)
18                 min = static_cast<int>(im->at<uchar>(Point(j, i)));
19         }
20     }
21 }

1 //自适应阈值 注：传入的只能是灰度图像
 2 void adapthreshold(Mat &image)
 3 {
 4     int max, min;    //保存最大和最小灰度值
 5     MaxGrayValue(image, max, min);   //计算出最大最小灰度值
 6     int grayvalue;    //用于暂时存取每个点的灰度值
 7     int Threshold = (max + min)/2;  //初始阈值
 8     int Temp_Threshold = Threshold; //用于存取每次迭代后的阈值
 9     int big_than_th;       //用于累加大于阈值的灰度值
10     int bigcount;           //用于存放大于阈值灰度值的像素点数量
11     int sma_than_th;       //用于累加小于阈值的灰度值
12     int smacount;           //用于存放小于阈值灰度值的像素点数量
13     Mat *im = reinterpret_cast<Mat*>((void*)&image);    //获取像素点信息
14     //Mat *im = &image;
15     int height = image.rows;   //获取图像高度
16     int width = image.cols;       //获取图像宽度
17
18
19     for (int k = 0; k < 50; k++)   //计算阈值，最大迭代50次
20     {
21         big_than_th = 0;
22         bigcount = 0;
23         sma_than_th = 0;
24         smacount = 0;
25         for (int i = 0; i < height; i++)
26         {
27             for (int j = 0; j < width; j++)
28             {
29                 grayvalue = static_cast<int>(im->at<uchar>(Point(j, i)));  //获取指定点灰度值
30                 if (grayvalue>Threshold)   //如果灰度值大于阈值，加到总灰度值，数量+1
31                 {
32                     big_than_th += grayvalue;
33                     bigcount++;
34                 }
35                 else if (grayvalue < Threshold) //如果灰度值小于阈值，加到总灰度值，数量+1
36                 {
37                     sma_than_th += grayvalue;
38                     smacount++;
39                 }
40             }
41         }
42         Temp_Threshold = ((big_than_th*1.0 / bigcount) + (sma_than_th*1.0 / smacount)) / 2;  //计算新的阈值
43         if (abs(Temp_Threshold - Threshold) < 2)   //如果新的阈值和旧的阈值差值的绝对值小于10，则退出
44             break;
45         else
46             Threshold = Temp_Threshold;    //否则旧阈值等于新阈值
47     }
48     for (int i = 0; i < height; i++)     //对图像进行二值化处理
49     {
50         uchar* data = image.ptr<uchar>(i);
51         for (int j = 0; j < width; j++)
52         {
53             grayvalue = static_cast<int>(im->at<uchar>(Point(j, i)));
54             if (grayvalue>Threshold)
55                 data[j] = 255;
56             else if (grayvalue < Threshold)
57                 data[j] = 0;
58         }
59     }
60 }

原文地址：https://www.cnblogs.com/Summerio/p/8280905.html