[人工智能]Opencv学习十二（自定义线性滤波）

各种算子

#include<opencv2/opencv.hpp>
#include<iostream>
#include<math.h>
#include <opencv2\imgproc\types_c.h>

using namespace cv;

int main(int argc, char** argv)
{
	Mat src,dst1,dst2,dst3,dst4,dst5;
	src = imread("2.jpg");
	if (!src.data)
	{
		printf("无\n");
		return -1;
	}
	char INPUT_WIN[] = "原图";
	char OUTPUT_WIN[] = "Robert X";
	char OUTPUT_DC[] = "Robert Y";
	namedWindow(INPUT_WIN, WINDOW_FREERATIO);
	namedWindow(OUTPUT_WIN, WINDOW_FREERATIO);
	namedWindow(OUTPUT_DC, WINDOW_FREERATIO);
	namedWindow("Sobel_X", WINDOW_FREERATIO);
	namedWindow("Sobel_Y", WINDOW_FREERATIO);
	namedWindow("拉普拉斯算子", WINDOW_FREERATIO);

	imshow(INPUT_WIN, src);

	// Robert X 方向  (逆时针45)
	Mat kernel = (Mat_<int>(2, 2) << 1, 0, 0, -1);
	filter2D(src, dst1, -1, kernel, Point(-1, -1), 0.0);
	imshow(OUTPUT_WIN, dst1);

	// Robert Y 方向(  顺时针45)
	Mat kernel2 = (Mat_<int>(2, 2) << 0, 1, -1, 0);
	filter2D(src, dst2, -1, kernel2, Point(-1, -1), 0.0);
	imshow(OUTPUT_DC, dst2);
	
	//Sobel算子  X
	Mat kernel_x= (Mat_<int>(3, 3) << -1, 0, 1, -2, 0, 2, -1, 0, 1);
	filter2D(src, dst3, -1, kernel_x, Point(-1, -1), 0.0);
	imshow("Sobel_X", dst3);
	//Sobel算子  Y
	Mat kernel_y = (Mat_<int>(3, 3) << -1, -2, -1, 0, 0, 0, 1, 2, 1);
	filter2D(src, dst4, -1, kernel_y, Point(-1, -1), 0.0);
	imshow("Sobel_Y", dst4);

	//拉普拉斯算子
	Mat kernel5= (Mat_<int>(3, 3) << 0, -1, 0, -1, 4, -1, 0, -1, 0);
	filter2D(src, dst5, -1, kernel5, Point(-1, -1), 0.0);
	imshow("拉普拉斯算子", dst5);

	waitKey(0);
	return 0;
}  

效果图

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?自定义卷积

#include<opencv2/opencv.hpp>
#include<iostream>
#include<math.h>
#include <opencv2\imgproc\types_c.h>

using namespace cv;

int main(int argc, char** argv)
{
	Mat src,dst;
	src = imread("2.jpg");
	if (!src.data)
	{
		printf("无\n");
		return -1;
	}
	char INPUT_WIN[] = "原图";
	namedWindow(INPUT_WIN, WINDOW_FREERATIO);
	namedWindow("自定义卷积", WINDOW_FREERATIO);

	imshow(INPUT_WIN, src);

	int c = 0;
	int index = 0;
	int ksize = 3;
	while (true)
	{
		c = waitKey(500);
		if ((char)c == 27) //ESC退出
		{
			break;
		}
		ksize = 4 + (index % 5) * 2 + 1;
		Mat kernel = Mat::ones(Size(ksize, ksize), CV_32F) / (float)(ksize * ksize);
		filter2D(src, dst, -1, kernel, Point(-1, -1));
		index++;
		imshow("自定义卷积", dst);
	}

	return 0;
}