Object Extraction and Measurement

I. Description of the problem
for the area and perimeter measurements photographed image of an object, the program is measured circumference and the area of the pixel, the practical problems in the process, and to scale transformation units.

II. Solutions
segmentation by processing the binary image morphology + + contour extraction

III. Source

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

using namespace cv;
using namespace std;

int main(int argc, char** argv)
{
	Mat srcImage = imread("E:\\pictures\\48.jpg");
 	if (srcImage.empty())
 	{
 		Mat srcImage = imread("E:\\pictures\\48.jpg");
 		if (srcImage.empty())
 		{
 			cout << "图像读取错误！" << endl;
  			return -1;
 		}
 		namedWindow("【1】原图", WINDOW_AUTOSIZE);
 		imshow("【1】原图", srcImage);
 	}

	//高斯模糊降噪
 	Mat blurImage;
 	GaussianBlur(srcImage, blurImage, Size(15, 15), 0, 0);
 	imshow("【2】高斯去噪后", blurImage);

	//二值化
 	Mat gray_srcImage, binary_srcImage;
 	cvtColor(blurImage, gray_srcImage, COLOR_BGR2GRAY);
 	threshold(gray_srcImage, binary_srcImage, 0, 255, THRESH_BINARY | THRESH_TRIANGLE);
 	//这里使用THRESH_TRIANGLE而不使用THRESH_OTSU的原因是该图像的直方图显示是一个单峰
 	imshow("【3】二值化后", binary_srcImage);

	//形态学操作
 	Mat morphImage;
 	Mat kernel = getStructuringElement(MORPH_RECT, Size(3, 3), Point(-1, -1));
 	morphologyEx(binary_srcImage, morphImage, MORPH_CLOSE, kernel, Point(-1, -1), 2);
 	//开操作是将边缘断开，闭操作是先膨胀后腐蚀，即将图像中的小洞填上
 	imshow("【4】形态学操作后", morphImage);

	//获取最大轮廓
 	vector<vector<Point>> contours;
 	vector<Vec4i> hireachy;
 	//findContours(morphImage, contours, hireachy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point());
 	findContours(morphImage, contours, hireachy, RETR_EXTERNAL, CHAIN_APPROX_SIMPLE, Point());
 	Mat contoursImage = Mat::zeros(srcImage.size(), CV_8UC3);
 	for (size_t t = 0; t < contours.size(); t++)
 	{
 		Rect rect = boundingRect(contours[t]);
  		if (rect.width < srcImage.cols / 2)//筛选出小于原图一般宽度尺寸的轮廓
  		{
  			continue;
  		}
  		double area = contourArea(contours[t]); //轮廓的面积
  		double length = arcLength(contours[t], true);  //轮廓的周长
  		drawContours(contoursImage, contours, static_cast<int>(t), Scalar(0, 0, 255), 1, 8, hireachy);
		//显示的数值是像素，实际中要与比例尺进行转换
  		cout << "轮廓的面积为：" << area << endl;
  		cout << "轮廓的周长为：" << length << endl;		
 	}
 	imshow("【5】效果图", contoursImage);

	waitKey(0);
 	return 0;
}

Output: