图像边缘检测，sobel，scharr

#include <opencv2/opencv.hpp>
#include <iostream>
#include <math.h>
using namespace cv;
using namespace std;

Mat src, dst,dst2,gray_src;
char* INPUT_WIN = "input image";
char* OUTPUT_WIN = "binary image";
int threshold_value = 127;
int threshold_max = 255;
int type_value = 2;
int type_max = 4;


int main()
{

    src = imread(".//pic//kate.png");

    namedWindow(INPUT_WIN, CV_WINDOW_AUTOSIZE);
    namedWindow(OUTPUT_WIN, CV_WINDOW_AUTOSIZE);
    imshow(INPUT_WIN, src);
    
    GaussianBlur(src, dst, Size(3, 3), 0, 0);
    Mat gray_src;
    cvtColor(dst, gray_src, CV_BGR2GRAY); 
    imshow(OUTPUT_WIN, gray_src);

    Mat xgrad, ygrad;
    //cv_16s 输出图像的深度
    //X方向1阶导,Y方向不求导
    //kernel大小是3
    /*Sobel(gray_src, xgrad, CV_16S, 1,0, 3);
    Sobel(gray_src, ygrad, CV_16S, 0, 1, 3);*/

    //Scharr算子:中心元素占的权重更重,边缘得到更大加强
    Scharr(gray_src, xgrad, CV_16S, 1, 0, 3);
    Scharr(gray_src, ygrad, CV_16S, 0, 1, 3);
    //图像增强
    convertScaleAbs(xgrad, xgrad,1.5,10);
    convertScaleAbs(ygrad, ygrad);
    imshow("xgrad", xgrad);
    imshow("ygrad", ygrad);

    //x,y方向都加进来
    Mat res;
    addWeighted(xgrad, 0.5, ygrad, 0.5, 0, res);
    imshow("res", res);
    

    waitKey(0);
    return 0; 
}