一、图像阈值化简介

二、固定阈值

三、自适应阈值

 #include<opencv2/opencv.hpp>

 using namespace cv;

 void main(){

     Mat src=imread("E://1.jpg",);//以灰度模式读入

     Mat dst;

     //threshold(src,dst,100,255,CV_THRESH_BINARY);

     //adaptiveThreshold(src,dst,255,CV_ADAPTIVE_THRESH_MEAN_C,CV_THRESH_BINARY,11,5);

     adaptiveThreshold(src,dst,,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,,);

     imshow("src",src);

     imshow("dst",dst);

     waitKey();

 }

四、滚动条调整参数

 #include<opencv2/opencv.hpp>

 using namespace cv;

 Mat src,dst,dst2;

 int thres_value=,block_size=,c=;

 void onThreshold(int ,void*){

     threshold(src,dst,thres_value,,CV_THRESH_BINARY);

     imshow("固定阈值",dst);

 }

 void onAdaptiveThreshold(int ,void *){

     if(block_size%==)    block_size++;//如果block_size是偶数

     adaptiveThreshold(src,dst2,,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,block_size,c);

     imshow("自适应阈值",dst2);

 }

 void main(){

     src=imread("E://1.jpg",);//以灰度模式读入

     namedWindow("固定阈值",CV_WINDOW_AUTOSIZE);

     namedWindow("自适应阈值",CV_WINDOW_AUTOSIZE);

     createTrackbar("Threshold", "固定阈值",&thres_value,,onThreshold,);

     createTrackbar("Block_size", "自适应阈值",&block_size,,onAdaptiveThreshold,);

     createTrackbar("C", "自适应阈值",&c,,onAdaptiveThreshold,);

     onThreshold(thres_value,); //回调函数初始化

     onAdaptiveThreshold(block_size,);

     onAdaptiveThreshold(c,);

     imshow("src",src);

     waitKey();

 }

opencv学习之路（13）、图像阈值化threshold的相关教程结束。