OpenCV实现Sobel边缘检测的示例

Sobel_x_or_y = cv2.Sobel(src, ddepth, dx, dy, dst, ksize, scale, delta, borderType)

#include <iostream>
#include <opencv2\opencv.hpp>

using namespace cv;
using namespace std;

int main()
{
	//----------------读取图像-----------------
	Mat img = imread("1.jpg");
	//黑白图像边缘检测结果较为明显
	Mat gray_img;
	cvtColor(img, gray_img, COLOR_BGR2GRAY);
	Mat resultX, resultY, resultXY;
	//-------------Sobel边缘检测--------------
	//X方向一阶边缘
	Sobel(img, resultX, CV_16S, 2, 0, 1);
	convertScaleAbs(resultX, resultX);

	//Y方向一阶边缘
	Sobel(img, resultY, CV_16S, 0, 1, 3);
	convertScaleAbs(resultY, resultY);

	//整幅图像的一阶边缘
	resultXY = resultX + resultY;

	//显示图像
	imshow("resultX", resultX);
	imshow("resultY", resultY);
	imshow("resultXY", resultXY);
	waitKey(0);
	return 0;
}

import cv2

img = cv2.imread("1.jpg")
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# -------------------Sobel边缘检测------------------------
x = cv2.Sobel(gray_img, cv2.CV_16S, 1, 0)
y = cv2.Sobel(gray_img, cv2.CV_16S, 0, 1)
# cv2.convertScaleAbs(src[, dst[, alpha[, beta]]])
# 可选参数alpha是伸缩系数，beta是加到结果上的一个值，结果返回uint类型的图像
Scale_absX = cv2.convertScaleAbs(x)  # convert 转换  scale 缩放
Scale_absY = cv2.convertScaleAbs(y)
result = cv2.addWeighted(Scale_absX, 0.5, Scale_absY, 0.5, 0)
# ----------------------显示结果----------------------------
cv2.imshow('img', gray_img)
cv2.imshow('Scale_absX', Scale_absX)
cv2.imshow('Scale_absY', Scale_absY)
cv2.imshow('result', result)
cv2.waitKey(0)
cv2.destroyAllWindows()