【OpenCV3】图像最大轮廓检测——cvFindBiggestContour()封装

此前在《【OpenCV3】图像轮廓查找与绘制——cv::findContours()与cv::drawContours()详解》一文中，详细介绍了图像轮廓的检测与绘制，但是在实际的应用中，往往需要检测目标的最大轮廓，但是OpenCV本身并没有封装这样一个函数，下面就贴上封装好的接口，供参考使用。

说明：对于最大轮廓的定义，有些以轮廓的点数最多为标准，有的以所包围的面积最大为标准，这里将两种都实现一下。

1、C接口的封装（最多点数）

CvSeq* cvFindBiggestCountour(IplImage *binaryImage)
{
	int polyHull0 = 1;
	CvPoint offset;
	offset.x = 0;
	offset.y = 0;

	CvMemStorage *tempStorage = cvCreateMemStorage(0);
	CvSeq *contour;
	CvSeq *c;

	int nContours = 0;
	double largest_length = 0;
	double len = 0;

	CvContourScanner scanner;
	CvSlice slice = CV_WHOLE_SEQ;
	scanner = cvStartFindContours(binaryImage, tempStorage, sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, offset);

	while ((c = cvFindNextContour(scanner)) != 0)
	{
		len = cvContourPerimeter(c);

		if (len > largest_length)
		{
			largest_length = len;
		}
	}

	scanner = cvStartFindContours(binaryImage, tempStorage, sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, offset);

	while ((c = cvFindNextContour(scanner)) != 0)
	{
		len = cvContourPerimeter(c);
		double q = largest_length;

		if (len < q)
			cvSubstituteContour(scanner, 0);

		else
		{
			CvSeq *newC;
			if (polyHull0)
				newC = cvApproxPoly(c, sizeof(CvContour), tempStorage, CV_POLY_APPROX_DP, 2, 0);
			else
				newC = cvConvexHull2(c, tempStorage, CV_CLOCKWISE, 1);

			cvSubstituteContour(scanner, newC);
		}
		nContours++;
	}
	printf("End find contours!\n");
	contour = cvEndFindContours(&scanner);
	cvReleaseMemStorage(&tempStorage);
	cvRelease(&c);
	return contour;
}

2、C接口的封装（最大面积）

CvSeq* cvFindBiggestCountour(IplImage *binaryImage)
{
	int polyHull0 = 1;
	CvPoint offset;
	offset.x = 0;
	offset.y = 0;

	CvMemStorage *tempStorage = cvCreateMemStorage(0);
	CvSeq *contour;
	CvSeq *c;

	int nContours = 0;
	double largest_length = 0;
	double len = 0;

	CvContourScanner scanner;
	CvSlice slice = CV_WHOLE_SEQ;
	scanner = cvStartFindContours(binaryImage, tempStorage, sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, offset);

	while ((c = cvFindNextContour(scanner)) != 0)
	{
		len = cvContourArea(c, slice, 0);

		if (len > largest_length)
		{
			largest_length = len;
		}
	}

	scanner = cvStartFindContours(binaryImage, tempStorage, sizeof(CvContour), CV_RETR_EXTERNAL, CV_CHAIN_APPROX_SIMPLE, offset);

	while ((c = cvFindNextContour(scanner)) != 0)
	{
		len = cvContourArea(c, slice, 0);
		double q = largest_length;

		if (len < q)
			cvSubstituteContour(scanner, 0);

		else
		{
			CvSeq *newC;
			if (polyHull0)
				newC = cvApproxPoly(c, sizeof(CvContour), tempStorage, CV_POLY_APPROX_DP, 2, 0);
			else
				newC = cvConvexHull2(c, tempStorage, CV_CLOCKWISE, 1);

			cvSubstituteContour(scanner, newC);
		}
		nContours++;
	}
	printf("End find contours!\n");
	contour = cvEndFindContours(&scanner);
	cvReleaseMemStorage(&tempStorage);
	cvRelease(&c);
	return contour;
}

3、C++接口封装（最多点数）

std::vector<cv::Point> findBiggestContour(cv::Mat binary_image)
{
	std::vector<std::vector<cv::Point>> contours;

	int largest_area = 0;
	int largest_contour_index = 0;

	cv::findContours(binary_image, contours, cv::noArray(), CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);

	for (int i = 0; i < contours.size(); i++)  
	{
		int a = contours[i].size();  
		if (a > largest_area){
			largest_area = a;
			largest_contour_index = i;               
		}
	}

	return contours[largest_contour_index];
}

4、C++接口封装（最大面积）

std::vector<cv::Point> findBiggestContour(cv::Mat binary_image)
{
	std::vector<std::vector<cv::Point>> contours;
	std::vector<cv::Vec4i> hierarchy;

	int largest_area = 0;
	int largest_contour_index = 0;

	cv::findContours(binary_image, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);

	for (int i = 0; i < contours.size(); i++) // iterate through each contour. 
	{
		double a = contourArea(contours[i], false);  //  Find the area of contour
		if (a > largest_area){
			largest_area = a;
			largest_contour_index = i;                //Store the index of largest contour
		}
	}

	return contours[largest_contour_index];
}

其中C++接口的测试代码如下

cv::Mat src = cv::imread("Hepburn.png", 1);
	cv::Mat result = src.clone();
	cv::Mat gray;
	cv::cvtColor(src, gray, CV_BGR2GRAY);
	cv::Mat binary;
	cv::threshold(gray, binary, 100, 255, cv::THRESH_BINARY);

	std::vector< std::vector< cv::Point> > contours;
	std::vector< cv::Point>  biggest_contour;
	std::vector< std::vector< cv::Point> > temp_contours;
	cv::findContours(
		binary,
		contours,
		cv::noArray(),
		cv::RETR_LIST,
		cv::CHAIN_APPROX_SIMPLE
		);
	biggest_contour = findBiggestContour(binary);
	temp_contours.push_back(biggest_contour);

	cv::drawContours(result, contours, -1, cv::Scalar(0, 255, 0));
	cv::drawContours(result, temp_contours, 0, cv::Scalar(0, 0, 255));

	cv::imshow("src", src);
	cv::imshow("gray", gray);
	cv::imshow("binary", binary);
	cv::imshow("result", result);
	cv::waitKey(0);

	return 0;

测试结果如下，其中红色曲线代表的是最大轮廓：

参考：https://harismoonamkunnu.blogspot.tw/2012/11/opencv-find-biggest-contour.html