opencv學習之路（13）、圖像閾值化threshold

一、圖像閾值化簡介

二、固定閾值

 三、自適應閾值

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

void main(){
    Mat src=imread("E://1.jpg",0);//以灰度模式讀入    
    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、滾動條調整參數

#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("固定閾值",dst);
}
void onAdaptiveThreshold(int ,void *){
    if(block_size%2==0)    block_size++;//如果block_size是偶數
    adaptiveThreshold(src,dst2,255,CV_ADAPTIVE_THRESH_GAUSSIAN_C,CV_THRESH_BINARY,block_size,c);
    imshow("自適應閾值",dst2);
}

void main(){
    src=imread("E://1.jpg",0);//以灰度模式讀入    
    namedWindow("固定閾值",CV_WINDOW_AUTOSIZE);
    namedWindow("自適應閾值",CV_WINDOW_AUTOSIZE);
    createTrackbar("Threshold", "固定閾值",&thres_value,255,onThreshold,0);
    createTrackbar("Block_size", "自適應閾值",&block_size,255,onAdaptiveThreshold,0);
    createTrackbar("C", "自適應閾值",&c,255,onAdaptiveThreshold,0);

    onThreshold(thres_value,0); //回調函數初始化
    onAdaptiveThreshold(block_size,0);
    onAdaptiveThreshold(c,0);

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