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:
- 图像去噪,高斯模糊
- 二值化
- 去除噪点,形态学操作,去除较小的噪点
- 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("case6.jpg");if (src.empty()){printf("colud not load image ..\n");return -1;}namedWindow(input_image, CV_WINDOW_AUTOSIZE);namedWindow(output_image, CV_WINDOW_AUTOSIZE);imshow(input_image, src);// 均值降噪Mat blurImg;GaussianBlur(src, blurImg, Size(15, 15), 0, 0);imshow("input image", src);// 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), 2);imshow("morphology", morphImage);// 获取最大轮廓vector<vector<Point>> contours;vector<Vec4i> hireachy;findContours(morphImage, contours, hireachy, CV_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