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",0);//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,255,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,11,5);
    imshow("src",src);
    imshow("dst",dst);
    waitKey(0);
}

 四、滚动条调整参数

#include<opencv2/opencv.hpp>
using namespace cv;

Mat src,dst,dst2;
int thres_value=21,block_size=5,c=5;

void onThreshold(int ,void*){
    threshold(src,dst,thres_value,255,CV_THRESH_BINARY);
    imshow("固定阈值",dst);
}
void onAdaptiveThreshold(int ,void *){
    if(block_size%2==0)    block_size++;//如果block_size是偶数
    adaptiveThreshold(src,dst2,255,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",0);//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,255,onThreshold,0);
    createTrackbar("Block_size", "自适应阈值",&block_size,255,onAdaptiveThreshold,0);
    createTrackbar("C", "自适应阈值",&c,255,onAdaptiveThreshold,0);

    onThreshold(thres_value,0); //回调函数初始化
    onAdaptiveThreshold(block_size,0);
    onAdaptiveThreshold(c,0);

    imshow("src",src);
    waitKey(0);
}