Opencv3笔记21——查找并绘制轮廓

一个轮廓一般对应一系列的点。也就是图像中的一条直线。

1. 寻找轮廓：findContours()函数

函数原型

void findContours(InputOutputArray image,OutputArrayOfArrays contours,OutputArray hierarchy,int mode,int method, Point offset=Point)

• 第四个参数，int类型的mode，轮廓检索模式
  

• 第五个参数
  

2. 绘制轮廓函数drawContours()

函数原型：

void drawCountours(InputOutputArray image,InputArrayOfArrays contours, int contourIdx,const Scalar & color,int thickness = 1, int lineType = 8, InputArrayhierarchy = noArray(),int maxLevel = INT_MAX,Point offset = Point())

3. 基础示例程序：轮廓查找

#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <vector>

using namespace cv;
using namespace std;

int main()
{
    //载入原始图
    Mat srcImage = imread("1.jpg", 0);

    //显示原始图
    imshow("原始图", srcImage);

    //初始化结果图
    Mat dstImage = Mat::zeros(srcImage.rows, srcImage.cols, CV_8UC3);

    //阈值化
    srcImage = srcImage > 119;
    imshow("阈值化后的原始图", srcImage);

    //定义轮廓和层次结构
    vector<vector<Point> >contours;
    vector<Vec4i> hierarchy;
    //查找轮廓

    findContours(srcImage, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);

    //遍历所有的顶层的轮廓，随机颜色绘制每个连接组件颜色

    int index = 0;

    for (; index >= 0; index = hierarchy[index][0])
    {
        Scalar color(rand() & 255, rand() & 255, rand() & 255);
        drawContours(dstImage, contours, index, color, FILLED, 8, hierarchy);
    }

    imshow("轮廓图", dstImage);
    waitKey(0);
    return 0;
}

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4. 综合示例

#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <iostream>

using namespace cv;
using namespace std;

//定义宏部分
#define WINDOW_NAME1 "【原始图窗口】"
#define WINDOW_NAME2 "【轮廓图】"

//定义全局变量
Mat g_srcImage;
Mat g_grayImage;
int g_nThresh = 80;
int g_nThresh_max = 255;
RNG g_rng(12345);
Mat g_cannyMat_output;
vector<vector<Point> > g_vContours;
vector<Vec4i> g_vHierarchy;

//全局函数
void on_ThreshChange(int, void *);

int main()
{
    //改变console字体颜色
    system("color 1F");

    //加载源图像
    g_srcImage = imread("1.jpg", 1);
    if (!g_srcImage.data)
    {
        printf("读取图片错误~！\n");
        return false;
    }

    //转成灰度并模糊降噪
    cvtColor(g_srcImage, g_grayImage, COLOR_BGR2GRAY);
    blur(g_grayImage, g_grayImage, Size(3, 3));

    //创建窗口
    namedWindow(WINDOW_NAME1, WINDOW_AUTOSIZE);
    imshow(WINDOW_NAME1, g_srcImage);

    //创建轨迹条
    createTrackbar("canny 阈值", WINDOW_NAME1, &g_nThresh, g_nThresh_max, on_ThreshChange);
    on_ThreshChange(0, 0);
    waitKey(0);
    return 0;
}

//on_ThreshChange()函数

void on_ThreshChange(int, void *)
{
    //调用canny算子检测边缘
    Canny(g_grayImage, g_cannyMat_output, g_nThresh, g_nThresh * 2, 3);

    //寻找轮廓
    findContours(g_cannyMat_output, g_vContours, g_vHierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));
    Mat drawing = Mat::zeros(g_cannyMat_output.size(), CV_8UC3);
    for (int i = 0; i < g_vContours.size(); i++)
    {
        Scalar color = Scalar(g_rng.uniform(0, 255), g_rng.uniform(0, 255), g_rng.uniform(0, 255));
        drawContours(drawing, g_vContours, i, color, 2, 8, g_vHierarchy, 0, Point());
    }
    imshow(WINDOW_NAME2, drawing);
}