OpenCV C++版图像阈值处理技巧

OpenCV是一个开源的计算机视觉库，它提供了大量的图像处理功能。在C++中使用OpenCV进行图像阈值处理时，可以利用其内置的函数来实现多种阈值处理技巧。

1. 简单阈值处理：

#include <opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main() {
    Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
    Mat dst;

    double threshold_value = 128;
    double max_value = 255;
    int threshold_type = THRESH_BINARY;

    threshold(src, dst, threshold_value, max_value, threshold_type);

    imwrite("output.jpg", dst);

    return 0;
}

2. 自适应阈值处理（Adaptive Thresholding）：

#include <opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main() {
    Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
    Mat dst;

    int block_size = 25;
    double constant = 5;
    int threshold_type = THRESH_BINARY;

    adaptiveThreshold(src, dst, 255, ADAPTIVE_THRESH_MEAN_C, threshold_type, block_size, constant);

    imwrite("output.jpg", dst);

    return 0;
}

3. Otsu阈值处理：

#include <opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main() {
    Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
    Mat dst;

    double threshold_value = 0;
    double max_value = 255;
    int threshold_type = THRESH_BINARY | THRESH_OTSU;

    threshold(src, dst, threshold_value, max_value, threshold_type);

    imwrite("output.jpg", dst);

    return 0;
}

4. 双峰阈值处理（Triangle Thresholding）：

#include <opencv2/opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

double triangleThreshold(Mat& src) {
    int hist[256] = {0};
    for (int i = 0; i < src.rows; i++) {
        for (int j = 0; j < src.cols; j++) {
            hist[src.at<uchar>(i, j)]++;
        }
    }

    int total = src.rows * src.cols;
    int accumulator[256] = {0};
    for (int i = 0; i < 256; i++) {
        accumulator[i] = hist[i] + (i == 0 ? 0 : accumulator[i - 1]);
    }

    double max_dist = 0;
    int threshold = 0;
    for (int i = 0; i < 256; i++) {
        if (accumulator[i] == 0 || accumulator[i] == total) continue;
        double dist = (double)(total - accumulator[i]) * i - (double)accumulator[i] * (255 - i);
        if (dist > max_dist) {
            max_dist = dist;
            threshold = i;
        }
    }

    return threshold;
}

int main() {
    Mat src = imread("input.jpg", IMREAD_GRAYSCALE);
    Mat dst;

    double threshold_value = triangleThreshold(src);
    double max_value = 255;
    int threshold_type = THRESH_BINARY;

    threshold(src, dst, threshold_value, max_value, threshold_type);

    imwrite("output.jpg", dst);

    return 0;
}

这些示例展示了如何在C++中使用OpenCV进行不同类型的图像阈值处理。你可以根据需要选择合适的阈值处理技巧。