opencv学习之路（13）、图像阈值化threshold

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();
 }