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在学习opencv的时候，对一张照片，需要标注照片上物体的不规则轮廓。

如图:

使用opencv进行物体的轮廓处理，关键在于对照片的理解，前期的照片处理的越好最后调用api出来的结果就越接近理想值。

提取照片中物体分如下三步：

1. 图像去噪，高斯模糊
2. 二值化
3. 去除噪点，形态学操作，去除较小的噪点
4. 进行轮廓查找

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>using namespace cv;
using namespace std;
Mat src, dst, gray_src;
char input_image[] = "input image";
char output_image[] = "output image";int main(int argc, char ** argv) {src = imread("d:/src.jpg");if (src.empty()) {printf("colud not load image ..\n");return -1;}//namedWindow(input_image, WINDOW_AUTOSIZE);//namedWindow(output_image, WINDOW_AUTOSIZE);imshow("input_image", src);// 均值降噪Mat blurImg;GaussianBlur(src, blurImg, Size(15, 15), 0, 0);imshow("GaussianBlur image", blurImg);// 二值化Mat binary;cvtColor(blurImg, gray_src, COLOR_BGR2GRAY);threshold(gray_src, binary, 0, 255, THRESH_BINARY | THRESH_TRIANGLE);imshow("binary", binary);// 闭操作进行联通物体内部Mat morphImage;Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));morphologyEx(binary, morphImage, MORPH_CLOSE, kernel, Point(-1, -1), 10);imshow("morphology", morphImage);// 获取最大轮廓vector<vector<Point>> contours;vector<Vec4i> hireachy;findContours(morphImage, contours, hireachy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point());Mat connImage = Mat::zeros(src.size(), CV_8UC3);for (size_t t = 0; t < contours.size(); t++) {Rect rect = boundingRect(contours[t]);if (rect.width < src.cols / 2) continue;if (rect.width > src.cols - 20) continue;double area = contourArea(contours[t]);double len = arcLength(contours[t], true);drawContours(connImage, contours, t, Scalar(0, 0, 255), 1, 8, hireachy);printf("area of star could : %f \n", area);printf("lenght of star could : %f \n", len);}imshow("output_image", connImage);waitKey(0);return 0;
}

二值化

形态学操作

最终的轮廓