opencv-canny边缘检测

最新推荐文章于 2025-06-21 01:04:26 发布

Digital2Slave

最新推荐文章于 2025-06-21 01:04:26 发布

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分类专栏： OpenCV opencv例程学习文章标签： OPENCV

本文链接：https://blog.youkuaiyun.com/tianzhaixing2013/article/details/8728865

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本文介绍了一个使用OpenCV库实现的Canny边缘检测算法程序。该程序首先读取一张彩色图像并将其转换为灰度图像，然后通过Canny算子检测图像中的边缘，并允许用户通过滑动条调整阈值来改变检测效果。

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#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include <stdlib.h>
#include <stdio.h>
#include <iostream>
using namespace cv;
using namespace std;

//全局变量
Mat src, src_gray;
Mat dst, detected_edges;

int edgeThresh = 1;
int lowThreshold;
int const max_lowThreshold = 100;
int ratio = 3;
int kernel_size = 3;
const char* window_name = "Edge Map";

/*
 * @function CannyThreshold
 * @brief Trackbar callback - Canny thresholds input with a ratio 1:3
 */
static void CannyThreshold(int, void*)
{
    /// Reduce noise with a kernel 3x3
    blur( src_gray, detected_edges, Size(3,3) );

    /// Canny detector
    Canny( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );

    /// Using Canny's output as a mask, we display our result
    dst = Scalar::all(0);

    src.copyTo( dst, detected_edges);
    imshow( window_name, dst );
}


/**
 * @function main
 */
int main( int, char** argv )
{
  /// Load an image
  //src = imread( argv[1] );
  src = imread("D:\\原始lena图像.bmp",CV_LOAD_IMAGE_COLOR);
  if( !src.data )
    { return -1; }

  /// Create a matrix of the same type and size as src (for dst)
  dst.create( src.size(), src.type() );

  /// Convert the image to grayscale
  cvtColor( src, src_gray, CV_BGR2GRAY );

  /// Create a window
  namedWindow( window_name, CV_WINDOW_AUTOSIZE );

  /// Create a Trackbar for user to enter threshold
  createTrackbar( "Min Threshold:", window_name, &lowThreshold, max_lowThreshold, CannyThreshold );

  /// Show the image
  CannyThreshold(0, 0);

  /// Wait until user exit program by pressing a key
  waitKey(0);

  return 0;
}