OpenCv - 轮廓练习二（8.1）

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本文介绍了如何在OpenCV3中处理图像轮廓，包括灰度化、二值化和轮廓查找步骤。同时，文章探讨了cvFindDominantPoints函数的替代方案，并在实践中展示了如何描述轮廓并检测图像的关键点。

OpenCV3 中cvFindDominantPoints 这个函数用什么替代了？

题目：用keynote画了一个图片，然后灰度化、二值化、查找轮廓，描述轮廓，最后查看关键点。

#include <iostream>
#include <opencv2/opencv.hpp>
#include <opencv2/highgui.hpp>

using namespace std;
using namespace cv;

#define CVX_RED   CV_RGB(0xff, 0x00, 0x00)
#define CVX_GREEN CV_RGB(0x00, 0xff, 0x00)
#define CVX_BLUE  CV_RGB(0x00, 0x00, 0xff)

int main()
{
    /*1、载入一个图像，转化为灰度图像*/
    const char filename[] = "/Users/linwang/Downloads/car_2/car_2.001.jpeg";
    IplImage * Gray_Img = cvLoadImage(filename,CV_LOAD_IMAGE_GRAYSCALE);
    cvShowImage("Gray", Gray_Img);
    
    /*2、二值化*/
    IplImage * D_V_Img = cvCreateImage(cvGetSize(Gray_Img), Gray_Img->depth, Gray_Img->nChannels);
    cvSetZero(D_V_Img);
    cvThreshold(Gray_Img, D_V_Img, 20, 255, CV_THRESH_BINARY);
    cvShowImage("D-V", D_V_Img);
    
    /*3、查找轮廓*/
    CvMemStorage * storage = cvCreateMemStorage();
    CvSeq * first_contour = NULL;
    cvFindContours(D_V_Img, storage, &first_contour,sizeof(CvContour),CV_RETR_LIST);
    cout<<"Total Point is "<<first_contour->total<<endl;
    for (int i = 0; i < first_contour->total; i++)
    {
        CvPoint *pt  = (CvPoint *) cvGetSeqElem(first_contour, i);
        cout<<"lunkuo Point : "<<pt->x<<" , "<<pt->y<<endl;
    }
    /*4、绘制轮廓*/
    cvDrawContours(D_V_Img, first_contour, 255, 255, 100);
    cvShowImage("Contours", D_V_Img);
    
    /*5、查找关键点*/
    
    IplImage * KeyImg = cvCreateImage(cvGetSize(D_V_Img), D_V_Img->depth, D_V_Img->nChannels);
    cvSetZero(KeyImg);
    CvSeq * dominant = NULL;
    //cvFindDominantPoints(first_contour,dominant);
    cout<<"Ap Poly Total is "<<dominant->total<<endl;
    for (int i = 0; i < dominant->total; i++)
    {
        CvPoint *pt  = (CvPoint *) cvGetSeqElem(dominant, i);
        cout<<"App Point : "<<pt->x<<" , "<<pt->y<<endl;
        cvCircle( KeyImg, *pt , 100, cvScalar(255) );
    }
    cvShowImage("Key-Points", KeyImg);
    
    cvWaitKey(0);
    cvReleaseImage(&KeyImg);
    cvReleaseImage(&D_V_Img);
    return 0;
}