threshold

2020-12-20

OpenCV中提供了阈值化函数threshold该函数原型如下：

double threshold(InputArray src,
                 OutputArray dst,
                 double thresh,
                 double maxval,
                 int type);

参数说明：

src ：表示输入图像

dst : 表示输出图像（尺寸和类型和输入图像一样）

thresh : 表示阈值

maxval : 表示预设最大值

type : 表示阈值化处理的类型设置（type类型有一下几种）

其枚举值如下：

enum ThresholdTypes {
    THRESH_BINARY     = 0,
    THRESH_BINARY_INV = 1, 
    THRESH_TRUNC      = 2, 
    THRESH_TOZERO     = 3, 
    THRESH_TOZERO_INV = 4, 
    THRESH_MASK       = 7,
    THRESH_OTSU       = 8, //!< flag, use Otsu algorithm to choose the optimal threshold value
    THRESH_TRIANGLE   = 16 //!< flag, use Triangle algorithm to choose the optimal threshold value
};

示例代码：

#include <iostream>
#include <string>
#include <cmath>
#include <opencv2/opencv.hpp>
using std::sin;
using std::cos;
//使用CommandLineParser对输入的参数进行分析，获取输入的图片路径
std::string GetFileName(int argc,char* argv[])
{
    /*
    argc : the size of argv[]
    argv : the parameters of comdline
    */
    const char* key = {
    "{help h usage? || usage information}"
    "{@picture || input picture}"
    };
     cv::CommandLineParser parser(argc,argv,key);
    if (parser.has("help"))
    {
        parser.printMessage();
        exit(0);
    }
    //如果没有输入图片路径
    if (!parser.check())
    {
        parser.printErrors();
        exit(-1);
    }
    std::string fileName = parser.get<std::string>(0);
    return fileName;
}

void onChange(int pos,void *userdata)
{
    cv::Mat dstImage;
    cv::Mat grayImage = *(cv::Mat*)userdata;
    cv::threshold(grayImage,dstImage,130,255,pos);
    cv::imshow("gray",dstImage);
}
int main(int argc,char* argv[])
{
    std::string fileName = GetFileName(argc,argv);
    cv::Mat srcImage = cv::imread(fileName);
    if (!srcImage.data)
    {
        std::cerr << " fail to load image" << std::endl;
        exit(-1);
    }
    cv::Mat grayImage;
    cv::cvtColor(srcImage,grayImage,cv::COLOR_BGR2GRAY);
    cv::namedWindow("gray");
    cv::imshow("gray",grayImage);
    cv::createTrackbar("threshold","gray",0,4,onChange,(void*)&grayImage);
    cv::imshow("srcImage",srcImage);
    cv::waitKey(0);
    cv::destroyAllWindows();
    return 0;
}