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使用c++實(shí)現(xiàn)OpenCV圖像橫向&縱向拼接

更新時間：2021年08月30日 15:38:38 作者：翟天保Steven

這篇文章主要介紹了使用c++實(shí)現(xiàn)OpenCV圖像橫向&縱向拼接，文中有圖像拼接函數(shù)，可以實(shí)現(xiàn)如“長圖拼接王”這類小程序的類似功能，大家可以將該函數(shù)封裝在軟件中自由使用

功能函數(shù)

// 圖像拼接
cv::Mat ImageSplicing(vector<cv::Mat> images,int type)
{
	if (type != 0 && type != 1)
		type = 0;
	
	int num = images.size();
	int newrow = 0;
	int newcol = 0;
	cv::Mat result;
 	// 橫向拼接
	if (type == 0)
	{
		int minrow = 10000;
		for (int i = 0; i < num; ++i)
		{
			if (minrow > images[i].rows)
				minrow = images[i].rows;
		}
		newrow = minrow;
		for (int i = 0; i < num; ++i)
		{
			int tcol = images[i].cols*minrow / images[i].rows;
			int trow = newrow;
			cv::resize(images[i], images[i], cv::Size(tcol, trow));
			newcol += images[i].cols;
			if (images[i].type() != images[0].type())
				images[i].convertTo(images[i], images[0].type());
		}
		result = cv::Mat(newrow, newcol, images[0].type(), cv::Scalar(255, 255, 255));
 		cv::Range rangerow, rangecol;
		int start = 0;
		for (int i = 0; i < num; ++i)
		{
			rangerow = cv::Range((newrow - images[i].rows) / 2, (newrow - images[i].rows) / 2 + images[i].rows);
			rangecol = cv::Range(start, start + images[i].cols);
			images[i].copyTo(result(rangerow, rangecol));
			start += images[i].cols;
		}
	}
	// 縱向拼接
	else if (type == 1) {
		int mincol = 10000;
		for (int i = 0; i < num; ++i)
		{
			if (mincol > images[i].cols)
				mincol = images[i].cols;
		}
		newcol = mincol;
		for (int i = 0; i < num; ++i)
		{
			int trow = images[i].rows*mincol / images[i].cols;
			int tcol = newcol;
			cv::resize(images[i], images[i], cv::Size(tcol, trow));
			newrow += images[i].rows;
			if (images[i].type() != images[0].type())
				images[i].convertTo(images[i], images[0].type());
		}
		result = cv::Mat(newrow, newcol, images[0].type(), cv::Scalar(255, 255, 255));
 
		cv::Range rangerow, rangecol;
		int start = 0;
		for (int i = 0; i < num; ++i)
		{
			rangecol= cv::Range((newcol - images[i].cols) / 2, (newcol - images[i].cols) / 2 + images[i].cols);
			rangerow = cv::Range(start, start + images[i].rows);
			images[i].copyTo(result(rangerow, rangecol));
			start += images[i].rows;
		}
	}
	return result;
}

測試代碼

#include <iostream>
#include <opencv2/opencv.hpp>
#include <vector>
using namespace std;
using namespace cv;
cv::Mat ImageSplicing(vector<cv::Mat> images, int type);
int main()
{
	cv::Mat src1 = imread("1.jpg");
	cv::Mat src2 = imread("2.jpg");
	cv::Mat src3 = imread("3.jpg");
	cv::Mat src4 = imread("4.jpg");
	vector<cv::Mat> images;
	images.push_back(src1);
	images.push_back(src2);
	images.push_back(src3);
	images.push_back(src4);
 
	// 0為橫向
	cv::Mat result1 = ImageSplicing(images, 0);
	// 1為縱向
	cv::Mat result2 = ImageSplicing(images, 1);
	imwrite("result1.jpg",result1);
	imwrite("result2.jpg",result2);
 	return 0;
}
// 圖像拼接
cv::Mat ImageSplicing(vector<cv::Mat> images,int type)
{
	if (type != 0 && type != 1)
		type = 0;
	int num = images.size();
	int newrow = 0;
	int newcol = 0;
	cv::Mat result;
 	// 橫向拼接
	if (type == 0)
	{
		int minrow = 10000;
		for (int i = 0; i < num; ++i)
		{
			if (minrow > images[i].rows)
				minrow = images[i].rows;
		}
		newrow = minrow;
		for (int i = 0; i < num; ++i)
		{
			int tcol = images[i].cols*minrow / images[i].rows;
			int trow = newrow;
			cv::resize(images[i], images[i], cv::Size(tcol, trow));
			newcol += images[i].cols;
			if (images[i].type() != images[0].type())
				images[i].convertTo(images[i], images[0].type());
		}
		result = cv::Mat(newrow, newcol, images[0].type(), cv::Scalar(255, 255, 255));
 
		cv::Range rangerow, rangecol;
		int start = 0;
		for (int i = 0; i < num; ++i)
		{
			rangerow = cv::Range((newrow - images[i].rows) / 2, (newrow - images[i].rows) / 2 + images[i].rows);
			rangecol = cv::Range(start, start + images[i].cols);
			images[i].copyTo(result(rangerow, rangecol));
			start += images[i].cols;
		}
	}
	// 縱向拼接
	else if (type == 1) {
		int mincol = 10000;
		for (int i = 0; i < num; ++i)
		{
			if (mincol > images[i].cols)
				mincol = images[i].cols;
		}
		newcol = mincol;
		for (int i = 0; i < num; ++i)
		{
			int trow = images[i].rows*mincol / images[i].cols;
			int tcol = newcol;
			cv::resize(images[i], images[i], cv::Size(tcol, trow));
			newrow += images[i].rows;
			if (images[i].type() != images[0].type())
				images[i].convertTo(images[i], images[0].type());
		}
		result = cv::Mat(newrow, newcol, images[0].type(), cv::Scalar(255, 255, 255));
 		cv::Range rangerow, rangecol;
		int start = 0;
		for (int i = 0; i < num; ++i)
		{
			rangecol= cv::Range((newcol - images[i].cols) / 2, (newcol - images[i].cols) / 2 + images[i].cols);
			rangerow = cv::Range(start, start + images[i].rows);
			images[i].copyTo(result(rangerow, rangecol));
			start += images[i].rows;
		}
	}
	
	return result;
}