使用C++语言阈值法对图像进行分割,全代码
时间: 2024-03-05 16:52:13 浏览: 18
好的,以下是使用C++语言阈值法对图像进行分割的全代码:
```
#include <opencv2/opencv.hpp>
#include <iostream>
using namespace cv;
using namespace std;
// 计算阈值
double otsu(Mat image)
{
int hist[256] = {0};
int pixelNum = image.rows * image.cols;
double sum = 0, sumB = 0, wB = 0, wF = 0, maxVar = 0, threshold = 0;
// 计算直方图
for(int i = 0; i < image.rows; i++)
{
for(int j = 0; j < image.cols; j++)
{
hist[int(image.at<uchar>(i,j))]++;
}
}
// 计算总和
for(int i = 0; i < 256; i++)
{
sum += i * hist[i];
}
// 计算类间方差
for(int i = 0; i < 256; i++)
{
wB += hist[i];
if(wB == 0) continue;
wF = pixelNum - wB;
if(wF == 0) break;
sumB += i * hist[i];
double mB = sumB / wB;
double mF = (sum - sumB) / wF;
double varBetween = wB * wF * pow(mB - mF, 2);
if(varBetween > maxVar)
{
maxVar = varBetween;
threshold = i;
}
}
return threshold;
}
// 分割图像
Mat thresholdImage(Mat image, double threshold)
{
Mat result = image.clone();
for(int i = 0; i < image.rows; i++)
{
for(int j = 0; j < image.cols; j++)
{
if(image.at<uchar>(i,j) > threshold)
result.at<uchar>(i,j) = 255;
else
result.at<uchar>(i,j) = 0;
}
}
return result;
}
int main()
{
Mat image = imread("image.jpg", IMREAD_GRAYSCALE);
if(image.empty())
{
cout << "Failed to read image!" << endl;
return -1;
}
double threshold = otsu(image);
Mat result = thresholdImage(image, threshold);
imshow("original", image);
imshow("result", result);
waitKey(0);
return 0;
}
```
其中,"image.jpg"是图像的路径,IMREAD_GRAYSCALE表示以灰度图像的方式读取图像。注意,要使用OpenCV库,需要在编译时链接OpenCV库。