1 //图像的阈值化
 2 #include<opencv2/opencv.hpp>
 3 using namespace cv;
 4 
 5 int main(){
 6     Mat src=imread("1.jpg",0);//以灰度模式读入
 7     Mat dst;
 8     //threshold(src,dst,100,255,CV_THRESH_BINARY);
 9     //adaptiveThreshold(src,dst,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,11,5);
10     adaptiveThreshold(src,dst,255,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,11,5);
11     imshow("src",src);
12     imshow("dst",dst);
13     waitKey(0);
14     return 0;
15 }

 1 //添加滚动条调整参数
 2 #include<opencv2/opencv.hpp>
 3 using namespace cv;
 4 
 5 Mat src,dst,dst2;
 6 int thres_value=21,block_size=5,c=5;
 7 
 8 void onThreshold(int ,void*){
 9     threshold(src,dst,thres_value,255,CV_THRESH_BINARY);
10     imshow("固定阈值",dst);
11 }
12 void onAdaptiveThreshold(int ,void *){
13     if(block_size%2==0)    block_size++;//如果block_size是偶数
14     adaptiveThreshold(src,dst2,255,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,block_size,c);
15     imshow("自适应阈值",dst2);
16 }
17 
18 int main(){
19     src=imread("1.jpg",0);//以灰度模式读入
20     namedWindow("固定阈值",CV_WINDOW_AUTOSIZE);
21     namedWindow("自适应阈值",CV_WINDOW_AUTOSIZE);
22     createTrackbar("Threshold", "固定阈值",&thres_value,255,onThreshold,0);
23     createTrackbar("Block_size", "自适应阈值",&block_size,255,onAdaptiveThreshold,0);
24     createTrackbar("C", "自适应阈值",&c,255,onAdaptiveThreshold,0);
25 
26     onThreshold(thres_value,0); //回调函数初始化
27     onAdaptiveThreshold(block_size,0);
28     onAdaptiveThreshold(c,0);
29 
30     imshow("src",src);
31     waitKey(0);
32     return 0;
33 }