OpenCV C++版圖像閾值處理技巧

OpenCV是一個開源的計算機視覺庫，它提供了大量的圖像處理功能。在C++中使用OpenCV進行圖像閾值處理時，可以利用其內(nèi)置的函數(shù)來實現(xiàn)多種閾值處理技巧。

1. 簡單閾值處理：

#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. 自適應閾值處理（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閾值處理：

#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. 雙峰閾值處理（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;
}

這些示例展示了如何在C++中使用OpenCV進行不同類型的圖像閾值處理。你可以根據(jù)需要選擇合適的閾值處理技巧。