用C++写一个灰度图直线检测代码

以下是一个简单的灰度图直线检测代码示例，使用C语言编写：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define WIDTH 640
#define HEIGHT 480

// 读入灰度图像
void read_gray_image(char* filename, unsigned char* image, int width, int height) {
    FILE* fp = fopen(filename, "rb");
    fread(image, sizeof(unsigned char), width * height, fp);
    fclose(fp);
}

// 保存检测结果
void save_image(char* filename, unsigned char* image, int width, int height) {
    FILE* fp = fopen(filename, "wb");
    fwrite(image, sizeof(unsigned char), width * height, fp);
    fclose(fp);
}

// 计算梯度幅值和角度
void calculate_gradient(unsigned char* image, int width, int height, unsigned char* gradient, float* angle) {
    int i, j, idx, gx, gy;
    float rad2deg = 180.0 / M_PI;

    for (i = 1; i < height - 1; i++) {
        for (j = 1; j < width - 1; j++) {
            idx = i * width + j;
            gx = image[idx + 1] - image[idx - 1];
            gy = image[idx + width] - image[idx - width];
            gradient[idx] = (unsigned char)sqrt(gx * gx + gy * gy);
            angle[idx] = atan2(gy, gx) * rad2deg;
        }
    }
}

// 直线检测
void detect_lines(unsigned char* gradient, float* angle, int width, int height, unsigned char* result) {
    int i, j, idx1, idx2, k, cnt, max_cnt, max_idx, max_theta, theta;
    float pi4 = M_PI / 4.0, rad2deg = 180.0 / M_PI;

    for (i = 1; i < height - 1; i++) {
        for (j = 1; j < width - 1; j++) {
            idx1 = i * width + j;
            if (gradient[idx1] > 50) { // 梯度幅值阈值
                max_cnt = 0;
                max_idx = -1;
                max_theta = -1;
                for (theta = 0; theta < 180; theta += 10) { // 角度分辨率
                    cnt = 0;
                    for (k = -4; k <= 4; k++) { // 线宽
                        idx2 = (i + k) * width + (j + (int)(tan(theta * M_PI / 180.0) * k));
                        if (idx2 >= 0 && idx2 < width * height && fabs(angle[idx1] - theta) < pi4) { // 角度容差
                            cnt += gradient[idx2];
                        }
                    }
                    if (cnt > max_cnt) {
                        max_cnt = cnt;
                        max_idx = idx1;
                        max_theta = theta;
                    }
                }
                if (max_idx >= 0) {
                    for (k = -4; k <= 4; k++) {
                        idx2 = (i + k) * width + (j + (int)(tan(max_theta * M_PI / 180.0) * k));
                        if (idx2 >= 0 && idx2 < width * height && fabs(angle[idx1] - max_theta) < pi4) { // 角度容差
                            result[idx2] = 255;
                        }
                    }
                }
            }
        }
    }
}

int main() {
    unsigned char image[WIDTH * HEIGHT];
    unsigned char gradient[WIDTH * HEIGHT];
    float angle[WIDTH * HEIGHT];
    unsigned char result[WIDTH * HEIGHT];

    read_gray_image("lena_gray.raw", image, WIDTH, HEIGHT);

    calculate_gradient(image, WIDTH, HEIGHT, gradient, angle);

    detect_lines(gradient, angle, WIDTH, HEIGHT, result);

    save_image("lena_lines.raw", result, WIDTH, HEIGHT);

    return 0;
}

注意：这只是一个简单的示例，可能不够完善。在实际应用中，需要根据具体情况进行调整和优化。