【图像轮廓与图像分割修复】

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前言

虽然Canny之类的边缘检测算法可以根据像素之间的差异，检测出轮廓边界的像素，但是它并没有将轮廓作为一个整体。

• 如何查找并绘制轮廓
• 如何寻找物体的凸包
• 如何使用多边形逼近物体
• 认识图像的矩
• 如何利用OpenCV进行图像修补

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1、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曲线，其表示方法可能根据不同的情况而有所不同。在OpenCV中可以用findContours()函数从二值图像中查找轮廓。

C++代码示例一

#include
#include
using namespace cv;

static void test()
{
	//1、载入原始图，且必须以二值图模式载入
	Mat srcImage = imread("69_1.jpg", 0);
	imshow("原始图", srcImage);

	//2、初始化结果图
	Mat dstImage = Mat::zeros(srcImage.rows, srcImage.cols, CV_8UC3);

	//3、srcImage取大于阈值119的那部分
	srcImage = srcImage > 119;
	imshow("取阈值后的原始图", srcImage);

	//4、定义轮廓和层次结构
	std::vector<std::vector<Point>> contours;
	std::vector<Vec4i> hierarchy;

	//5、查找轮廓
	findContours(srcImage, contours, hierarchy, RETR_CCOMP, CHAIN_APPROX_SIMPLE);

	//6、遍历所有顶层的轮廓，以随机颜色绘制出每个连接组件颜色
	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);
	}

	//7、显示最后的轮廓图
	imshow("轮廓图", dstImage);
	waitKey(0);
}

int main()
{
	test();
	system("pause");
	return 0;
}

结果

C++代码示例二

#include
#include
#include
using namespace cv;

static std::string windows_name1 = "【原始图窗口】";
static std::string windows_name2 = "【轮廓图】";

static Mat g_srcImage, g_grayImage, g_cannyMat_output;
static int g_nThresh = 80, g_nThresh_max = 255;
static RNG g_rng(12345);
std::vector<std::vector<Point>> g_vContours;
std::vector<Vec4i> g_vHierarchy;

static void on_ThreshChange(int, void*);

static void test()
{
	//1、改变console字体颜色
	system("color 1F");
	//2、加载源图像
	g_srcImage = imread("70_1.jpg", 1);
	if (!g_srcImage.data) {
		std::cout << "image not load" << std::endl;
		return;
	}

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

	//4、创建窗口
	namedWindow(windows_name1, WINDOW_AUTOSIZE);
	imshow(windows_name1, g_srcImage);

	//5、创建滚动条并初始化
	createTrackbar("canny阈值", windows_name1, &g_nThresh, g_nThresh_max, on_ThreshChange);
	on_ThreshChange(0, 0);
	waitKey(0);

}

int main()
{
	test();
	system("pause");
	return 0;
}

void on_ThreshChange(int, void *)
{
	//1、用于Canny算子检测边缘
	Canny(g_grayImage, g_cannyMat_output, g_nThresh, g_nThresh * 2, 3);
	//2、寻找轮廓
	findContours(g_cannyMat_output, g_vContours, g_vHierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));

	//3、绘出轮廓
	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());
	}
	//显示效果图
	imshow(windows_name2, drawing);
}

结果

2、寻找物体的凸包

凸包(Convex Hull)是一个计算机中常见的概念。简单来说，给定二维平面上的点集，凸包就是将最外层的点连接起来构造成的凸多边形，它是能包含点集中所有点的。

C++代码示例一

#include
#include
#include
using namespace cv;

static void test()
{
	//初始化变量和随机值
	Mat image(600, 600, CV_8UC3);
	RNG& rng = theRNG();

	//循环，按下ESC,Q,q键程序退出，否则有键按下便一直更新
	while (1) {
		//参数初始化
		char key;  //键值
		int count = (unsigned)rng % 100 + 3; //随机生成点的数量
		std::vector<Point>points;   //点值

		//随机生成点坐标
		for (int i = 0; i < count; i++) {
			Point point;
			point.x = rng.uniform(image.cols / 4, image.cols * 3 / 4);
			point.y = rng.uniform(image.rows / 4, image.rows * 3 / 4);

			points.push_back(point);
		}

		//检测凸包
		std::vector<int> hull;
		convexHull(Mat(points), hull, true);

		//绘制出随机颜色的点
		image = Scalar::all(0);
		for (int i = 0; i < count; i++)
			circle(image, points[i], 3, Scalar(rng.uniform(0, 255),
				rng.uniform(0, 255), rng.uniform(0, 255)), FILLED, LINE_AA);
		//准备参数
		int hullcount = (int)hull.size();  //凸包的边数
		Point point0 = points[hull[hullcount - 1]];  //连接凸包边的坐标点

		//绘制凸包的边
		for (int i = 0; i < hullcount; i++)
		{
			Point point = points[hull[i]];
			line(image, point0, point, Scalar(255, 255, 255), 2, LINE_AA);
			point0 = point;
		}

		//显示效果图
		imshow("凸包检测示例", image);

		//按下ESC,Q,q，程序退出
		key = (char)waitKey();
		if (key == 27 || key == 'q' || key == 'Q')
			break;
	}
}


int main()
{
	test();
	system("pause");
	return 0;
}

结果

C++代码示例二

#include
#include
#include
using namespace cv;

static std::string window_name1 = "【原始图窗口】";
static std::string window_name2 = "【效果图窗口】";

static Mat g_srcImage, g_grayImage, g_thresholdImage_output;
static int g_nThresh = 50, g_maxThresh = 255;
static RNG g_rng(12345);
static Mat srcImage_copy = g_srcImage.clone();

static std::vector<std::vector<Point>> g_vContours;
static std::vector<Vec4i> g_vHierarchy;

static void on_ThreshChange1(int, void*);


static void test()
{
	//1、加载源图像
	g_srcImage = imread("72_1.jpg", 1);

	//2、将原图转换成灰度图并进行模糊降噪
	cvtColor(g_srcImage, g_grayImage, COLOR_BGR2GRAY);
	blur(g_grayImage, g_grayImage, Size(3, 3));

	//3、创建原图窗口并显示
	namedWindow(window_name1, WINDOW_AUTOSIZE);
	imshow(window_name1, g_srcImage);

	//4、创建滚动条
	createTrackbar("阈值:", window_name1, &g_nThresh, g_maxThresh, on_ThreshChange1);
	on_ThreshChange1(0, 0);
	waitKey(0);
}

int main()
{
	test();
	system("pause");
	return 0;
}

void on_ThreshChange1(int, void *)
{
	//对图像进行二值化控制阈值
	threshold(g_grayImage, g_thresholdImage_output, g_nThresh, 255, THRESH_BINARY);
	//寻找轮廓
	findContours(g_thresholdImage_output, g_vContours, g_vHierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0, 0));

	//遍历每个轮廓，寻找其凸包
	std::vector<std::vector<Point>> hull(g_vContours.size());
	for (unsigned int i = 0; i < g_vContours.size(); i++)
		convexHull(Mat(g_vContours[i]), hull[i], false);

	//绘出轮廓及其凸包
	Mat drawing = Mat::zeros(g_thresholdImage_output.size(), CV_8UC3);
	for (unsigned 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, 1, 8, std::vector<Vec4i>(), 0, Point());
		drawContours(drawing, hull, i, color, 1, 8, std::vector<Vec4i>(), 0, Point());
	}
	//显示效果图
	imshow(window_name2, drawing);
}

结果

3、使用多边形将轮廓包围

在实际应用中，常常会有将检测到的轮廓用多边形表示出来的需求。

• 返回外部矩形边界：boundingRect()函数
• 寻找最小包围矩形：minAreaRect()函数
• 寻找最小包围圆形：minEnclosingCircle()函数
• 用椭圆拟合二维点集：fitEllipse()函数
• 逼近多边形曲线：approxPolyDP()函数

结果

C++代码示例一

#include
#include
#include
using namespace cv;

static void  test()
{
	//1、改变console字体颜色
	system("color 1F");

	//2、初始化变量和随机值
	Mat image(600, 600, CV_8UC3);
	RNG& rng = theRNG();

	//3、循环，按下ESC,Q,q键程序退出，否则有键按下便一直更新
	while (1)
	{
		//参数初始化
		int count = rng.uniform(3, 103);//随机生成点的数量
		std::vector<Point> points;//点值

		//随机生成点坐标
		for (int i = 0; i < count; i++)
		{

			Point point;
			point.x = rng.uniform(image.cols / 4, image.cols * 3 / 4);
			point.y = rng.uniform(image.rows / 4, image.rows * 3 / 4);

			points.push_back(point);
		}

		//对给定的 2D 点集，寻找最小面积的包围矩形
		RotatedRect box = minAreaRect(Mat(points));
		Point2f vertex[4];
		box.points(vertex);

		//绘制出随机颜色的点
		image = Scalar::all(0);
		for (int i = 0; i < count; i++)
			circle(image, points[i], 3, Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), FILLED, LINE_AA);

		//绘制出最小面积的包围矩形
		for (int i = 0; i < 4; i++)
			line(image, vertex[i], vertex[(i + 1) % 4], Scalar(100, 200, 211), 2, LINE_AA);

		//显示窗口
		imshow("矩形包围示例", image);

		//按下ESC,Q,或者q，程序退出
		char key = (char)waitKey();
		if (key == 27 || key == 'q' || key == 'Q') // 'ESC'
			break;
	}
}

int main()
{
	test();
	system("pause");
	return 0;
}

结果

C++代码示例二

#include
#include
#include
using namespace cv;

static void test()
{
	//改变console字体颜色
	system("color 1F");

	//初始化变量和随机值
	Mat image(600, 600, CV_8UC3);
	RNG& rng = theRNG();

	//循环，按下ESC,Q,q键程序退出，否则有键按下便一直更新
	while (1)
	{
		//参数初始化
		int count = rng.uniform(3, 103);//随机生成点的数量
		std::vector<Point> points;//点值

		//随机生成点坐标
		for (int i = 0; i < count; i++)
		{

			Point point;
			point.x = rng.uniform(image.cols / 4, image.cols * 3 / 4);
			point.y = rng.uniform(image.rows / 4, image.rows * 3 / 4);

			points.push_back(point);
		}

		//对给定的 2D 点集，寻找最小面积的包围圆
		Point2f center;
		float radius = 0;
		minEnclosingCircle(Mat(points), center, radius);

		//绘制出随机颜色的点
		image = Scalar::all(0);
		for (int i = 0; i < count; i++)
			circle(image, points[i], 3, Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), FILLED, LINE_AA);


		//绘制出最小面积的包围圆
		circle(image, center, cvRound(radius), Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255)), 2, LINE_AA);

		//显示窗口
		imshow("圆形包围示例", image);

		//按下ESC,Q,或者q，程序退出
		char key = (char)waitKey();
		if (key == 27 || key == 'q' || key == 'Q') // 'ESC'
			break;
	}
}

int main()
{
	test();
	system("pause");
	return 0;
}