OpenCV函数图像基本操作_opencv中图像函数该怎么声明-优快云博客

本文详细介绍了使用OpenCV进行图像处理的方法，包括读取和显示图像、灰度转换、图像大小调整、创建图像、图像保存及像素访问等关键操作。通过具体代码示例，展示了如何利用OpenCV库实现图像的基本处理功能。

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#include<iostream>
#include<opencv2\opencv.hpp>
using namespace std;
using namespace cv;
int main()
{
	Mat image_test,image_gray,image_resize,image_rotate;
	Size test_size;
	test_size.height = 80;
	test_size.width = 100;
	//convert image to 3 channels:BGR
	image_test = imread("front.bmp", IMREAD_UNCHANGED);
	//灰度图变换
	cvtColor(image_test, image_gray, CV_BGR2GRAY);
	//图片大小重置
	resize(image_test, image_resize, test_size, (0, 0), (0, 0), INTER_LINEAR);
	//创建图片
	Mat image_create3(2, 2, CV_8UC3, Scalar(0, 0, 255));
	Mat image_create1(2, 2, CV_8UC1, Scalar(50));
	//图片写到本地
	vector<int> compression_params;
	compression_params.push_back(CV_IMWRITE_JPEG_QUALITY);
	compression_params.push_back(100);
	imwrite("../../images/imwrite_test.jpg", image_resize, compression_params);
	//opencv中像素值存放次序依次是：b,g,r
	//第1种：指针访问，速度最快
	uchar B, G, R;
	for (int i = 0; i < image_test.rows; i++)
	{
		for (int j = 0; j < image_test.cols; j++)
		{
			B = image_test.ptr<Vec3b>(i)[j][0];
			G = image_test.ptr<Vec3b>(i)[j][1];
			R = image_test.ptr<Vec3b>(i)[j][2];
		}
	}
	B = image_gray.ptr<uchar>(200)[200];
	//第2种：迭代器访问
	for (int i = 0; i < image_test.rows; i++)
		for (int j = 0; j < image_test.cols; j++)
		{
			image_test.at<Vec3b>(i, j)[0] = 0;
			image_test.at<Vec3b>(i, j)[1] = 0;
			image_test.at<Vec3b>(i, j)[2] = 255;
		}
	return 0;
}