1、尺寸變換

1.1 圖像差值原理

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1.2 圖像縮放、翻轉(zhuǎn)、拼接

1.2.1 圖像縮放

?1.2.2 圖像翻轉(zhuǎn)

1.2.3 圖像拼接

#include <iostream>
#include <fstream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main()
{
	Mat gray = imread(" lena.png",IMREAD_GRAYSCALE);
	Mat sma1lImg,bigImg0,biglmg1,bigImg2;
	resize(gray, sma1lImg,Size(15, 15), 0, 0, INTER_AREA);//先將圖像縮小resize(smalllmg，bigImg0，Size(30，30)，0，0，INTER_NEAREST);//最近鄰差值resize(smallImg，bigImgl，Size(30，30)，0，0，INTER_LINEAR);//雙線性差值resize(smalllmg，bigImg2，Size(30，30)，0，0，INTER_CUBIC);//雙三次差值
	Mat img_x,img_y,img_xy;
	flip(gray,img_x,0);// 沿x軸對稱
	flip(gray,img_y,1);//沿y軸對稱
	flip(gray,img_xy, -1); //先x軸對稱，再y軸對稱
	Mat img00 = imread("lena00.png");
	Mat img01 = imread("lena01.png"); 
	Mat img10 = imread("lena10.png") ;
	Mat imgl1 = imread("lenal1.png" );

	//圖像連接
	Mat img,img0,imgl;//圖像橫向連接
	hconcat(img00,img01,img0);
	hconcat(img10, imgl1, imgl);//橫向連接結(jié)果再進(jìn)行豎向連接
	vconcat(img0, imgl, img);

	waitKey(0);
	system("pause");
	return 0;
}

2、仿射變換

2.1 仿射變換原理

?2.2 仿射變換函數(shù)

?2.3 邊界填充方法和對應(yīng)標(biāo)志

?2.4 圖像旋轉(zhuǎn)

?2.5 計(jì)算仿射變換矩陣

?

//仿射變換
int affineConversion(void)
{
	Mat img = imread("F:/testMap/lena.png");
	if (img.empty())
	{
		cout << "請確認(rèn)圖像文件名稱是否正確" << endl;
		return -1;
	}
	
	Mat rotation0, img_warp0;
	double angle = 45;//設(shè)置圖像旋轉(zhuǎn)的角度
	Size dst_size(img.rows, img.cols);//設(shè)置輸出圖像的尺寸
	Point2f center(img.rows/2.0,img.cols/2.0);//設(shè)置圖像的旋轉(zhuǎn)中心

	rotation0 = getRotationMatrix2D(center,angle,1);//計(jì)算仿射變換矩陣
	
	warpAffine(img,img_warp0,rotation0,dst_size);//進(jìn)行仿射變換
	imshow("img_warp0", img_warp0);

	//根據(jù)定義的三個(gè)點(diǎn)進(jìn)行仿射變換
	Point2f src_points[3];
	Point2f dst_points[3];
	src_points[0] = Point2f(0,0);//原始圖像中的三個(gè)點(diǎn)
	src_points[1] = Point2f(0,(float)(img.cols - 1));
	src_points[2] = Point2f((float)(img.rows - 1),(float)(img.cols - 1));
	dst_points[0] = Point2f((float)(img.rows)*0.11,(float)(img.cols)*0.20);//放射變換后圖像中的三個(gè)點(diǎn)
	dst_points[1] = Point2f((float)(img.rows)*0.15,(float)(img.cols)*0.70);
	dst_points[2] = Point2f((float)(img.rows)*0.81,(float)(img.cols)*0.85);
	
	Mat rotation1,img_warpl;
	rotation1 = getAffineTransform(src_points, dst_points);//根據(jù)對應(yīng)點(diǎn)求取仿射變換矩陣
	warpAffine(img,img_warpl,rotation1,dst_size);//進(jìn)行仿射變換
	imshow("img_warpl", img_warpl);
	waitKey(0);
}

3、透視變換

3.1 原理

?3.2 計(jì)算透視變化矩陣函數(shù)

?4個(gè)像素坐標(biāo)，圖有誤

3.3 計(jì)算方法標(biāo)志

?3.4 透視變換函數(shù)

?

//透視變換
int perspectiveConversion(void)
{
	Mat img = imread("F:/testMap/二維碼.png");
	if (img.empty())
	{
		cout << "請確認(rèn)圖像文件名稱是否正確" << endl;
		return -1;
	}

	Point2f src_points[4]; 
	Point2f dst_points[4];
	
	//通過Image Watch查看的二維碼四個(gè)角點(diǎn)坐標(biāo)
	src_points[0] = Point2f(100.0,401.0);
	src_points[1] = Point2f(551.0,403.0);
	src_points[2] = Point2f(1.0,676.0);
	src_points[3] = Point2f(684.0,678.0);
	
	//期望透視變換后二維碼四個(gè)角點(diǎn)的坐標(biāo)
	dst_points[0] = Point2f(0.0,0.0);
	dst_points[1] = Point2f(627.0,0.0);
	dst_points[2] = Point2f(0.0, 627.0);
	dst_points[3] = Point2f(627.0,627.0);
	
	Mat rotation,img_warp;
	rotation = getPerspectiveTransform(src_points,dst_points);//計(jì)算透視變換矩陣
	warpPerspective(img,img_warp,rotation,img.size());//透視變換投影
	imshow("img",img);
	imshow("img_warp",img_warp);
	
	waitKey(0);
}

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