使用 OpenCV C++ 查找已知对象

Posted 2023-02-21

【中文标题】使用 OpenCV C++ 查找已知对象

【英文标题】：Finding a known object with OpenCV C++

【发布时间】：2016-03-09 16:41:50

【问题描述】：

我是 OpenCV 的新手。我在 Visual Studio 2013，Windows 10 上使用 OpenCV - 2.4.12。我正在尝试创建一个程序，它将 2 个图像作为输入，并尝试在第 2 个图像中找到类似的第 1 个图像块。通过查找功能和 Homography.. 基本上我正在关注 This 教程。并成功实现了代码。所以我想更进一步，我想裁剪匹配的块......所以，我成功创建了一个蒙版图像，但是当我尝试 bitwise_and 或类似的东西时，它显示以下错误。

Unhandled exception at 0x772FD928 in OpenCVTut.exe Microsoft C++ exception: cv::Exception at memory location 0x0017E6C0.

我尝试了很多谷歌搜索...但找不到任何解决方案。以下是代码，以及我正在使用的图像和我生成的掩码..

#include <iostream>
#include <opencv2\opencv.hpp>
#include <opencv2\core\core.hpp>
#include <opencv2\highgui\highgui.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\calib3d\calib3d.hpp>
#include <opencv2\features2d\features2d.hpp>
#include <opencv2\nonfree\nonfree.hpp>

using namespace std;
using namespace cv;


int main() 
    Mat imgObject = cvLoadImage("E:/opencv/images/Experiments/target.jpg", CV_LOAD_IMAGE_GRAYSCALE);
    Mat imgScene = cvLoadImage("E:/opencv/images/Experiments/source.jpg", CV_LOAD_IMAGE_GRAYSCALE);

    if (!imgObject.data || !imgScene.data) 
        cout << "Error reading images" << endl;

        return -1;
    

    int minHessian = 400;
    SurfFeatureDetector detector(minHessian);
    vector<KeyPoint> keyPointsObject;
    vector<KeyPoint> keyPointsScene;

    detector.detect(imgObject, keyPointsObject);
    detector.detect(imgScene, keyPointsScene);

    SurfDescriptorExtractor extractor;
    Mat descriptorObject;
    Mat descriptorScene;

    extractor.compute(imgObject, keyPointsObject, descriptorObject);
    extractor.compute(imgScene, keyPointsScene, descriptorScene);

    FlannBasedMatcher matcher;
    vector<DMatch> matches;
    matcher.match(descriptorObject, descriptorScene, matches);

    double maxDist = 0;
    double minDist = 100;

    for (int i = 0; i < descriptorObject.rows; i++) 
        double dist = matches[i].distance;

        if (dist > maxDist) maxDist = dist;
        if (dist < minDist) minDist = dist;
    

    cout << "-- Max dist : " << maxDist << endl;
    cout << "-- Min dist : " << minDist << endl;

    vector<DMatch> goodMatches;
    for (int i = 0; i < descriptorObject.rows; i++) 
        if (matches[i].distance < 3 * minDist) 
            goodMatches.push_back(matches[i]);
        
    

    /*Mat imgMatches;
    drawMatches(imgObject, keyPointsObject, imgScene, keyPointsScene,
        goodMatches, imgMatches, Scalar::all(-1), Scalar::all(-1),
        vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS);*/

    vector<Point2f> obj;
    vector<Point2f> scene;

    for (int i = 0; i < goodMatches.size(); i++) 
        obj.push_back(keyPointsObject[goodMatches[i].queryIdx].pt);
        scene.push_back(keyPointsScene[goodMatches[i].trainIdx].pt);
    

    Mat H = findHomography(obj, scene, CV_RANSAC);

    vector<Point2f> objCorners(4);
    objCorners[0] = cvPoint(0, 0);
    objCorners[1] = cvPoint(imgObject.cols, 0);
    objCorners[2] = cvPoint(imgObject.cols, imgObject.rows);
    objCorners[3] = cvPoint(0, imgObject.rows);

    vector<Point2f> sceneCorners(4);
    perspectiveTransform(objCorners, sceneCorners, H);

    line(imgScene, sceneCorners[0], sceneCorners[1], Scalar(0, 255, 0), 4);
    line(imgScene, sceneCorners[1], sceneCorners[2], Scalar(0, 255, 0), 4);
    line(imgScene, sceneCorners[2], sceneCorners[3], Scalar(0, 255, 0), 4);
    line(imgScene, sceneCorners[3], sceneCorners[0], Scalar(0, 255, 0), 4);

    Mat mask = Mat::zeros(imgScene.rows, imgScene.cols, CV_8UC3);
    vector< vector<Point> > contours;
    vector< Vec4i > hierarchy;

    Mat coun;
    imgScene.copyTo(coun);
    findContours(coun, contours, hierarchy, CV_RETR_CCOMP, CV_CHAIN_APPROX_SIMPLE);

    Scalar color(255, 255, 255);
    drawContours(mask, contours, 0, color, CV_FILLED, 8, hierarchy);

    Mat element = getStructuringElement(MORPH_RECT, Size(2, 2), Point(0, 0));
    dilate(mask, mask, element);
    erode(mask, mask, element);

    Mat res(imgScene.rows, imgScene.cols, CV_8UC1, Scalar(0, 0, 0));
    bitwise_and(imgScene, mask, res);

    namedWindow("Good Matches & Object detection", CV_WINDOW_AUTOSIZE);
    imshow("Good Matches & Object detection", mask);

    waitKey(0);

    return 0;

场景

目标

面具

那么，谁能解释一下这个错误......以及我需要做些什么来解决它......

提前致谢:)

【问题讨论】：

您可以先检查在抛出此异常时中断的选项，然后自己看看为什么会抛出它。

@StoryTeller。也试过了......如果这很有意义，我不会在这里问......：p :'）......就像我说的......我在opencv中很新，或者更有可能是计算机视觉。

请找到发生错误的代码行。偶尔使用调试器或 std::cout 一条独特的消息。

@Micka... 我很确定错误在“bitwise_and(imgScene, mask, res);”中这一行……​​

【参考方案1】：

错误发生在以下行：

bitwise_and(imgScene, mask, res);

因为这两个矩阵的类型不同：imgScene 是 CV_8UC1 矩阵，mask 是 CV_8UC3。

由于掩码通常只是一个二进制图像，可以用单通道矩阵安全地表示，您可以修复您的代码，使maskCV_8UC1 矩阵：

Mat mask = Mat::zeros(imgScene.rows, imgScene.cols, CV_8UC1); // Instead of CV_8UC3

【讨论】：

谢谢人...你是一个救生员 :D 很抱歉迟到的回应，搞砸了一些配置...不得不解决这个问题... :) ...非常感谢您的帮助。 .. :)