Question

这是我的代码（从zindarod获取输入后工作）

 #include <stdio.h>
#include "opencv2/core/core.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/nonfree/nonfree.hpp"

using namespace cv;

static void help()
{
    printf("\nThis program demonstrates using features2d detector, descriptor extractor and simple matcher\n"
            "Using the sift desriptor:\n"
            "\n"
            "Usage:\n matcher_simple <image1> <image2>\n");
}

int main(int argc, char** argv)
{
    if(argc != 3)
    {
        help();
        return -1;
    }

    Mat img1 = imread(argv[1], CV_LOAD_IMAGE_GRAYSCALE);
    Mat img2 = imread(argv[2], CV_LOAD_IMAGE_GRAYSCALE);
 Rect regionone(151, 115, 42, 27);  
 Rect regiontwo(141, 105, 52, 37);  
Mat dst,mask;
Rect rect(151, 115, 42, 27);
mask = Mat::zeros(img1.size(),CV_8UC1);
mask(Rect(151,115,42,27)) = 1;
img1.copyTo(dst,mask);
    if(img1.empty() || img2.empty())
    {
        printf("Can't read one of the images\n");
        return -1;
    }

    // detecting keypoints
    SiftFeatureDetector detector(400);
    vector<KeyPoint> keypoints1, keypoints2;
    detector.detect(dst, keypoints1);
    detector.detect(img2, keypoints2);

    // computing descriptors
    SiftDescriptorExtractor extractor;
    Mat descriptors1, descriptors2;
    extractor.compute(dst, keypoints1, descriptors1);
    extractor.compute(img2, keypoints2, descriptors2);

    // matching descriptors
    BFMatcher matcher(NORM_L2);
    vector<DMatch> matches;
    matcher.match(descriptors1, descriptors2, matches);

    // drawing the results
    namedWindow("matches", 1);
    Mat img_matches;
    drawMatches(dst, keypoints1, img2, keypoints2, matches, img_matches);
imshow("masked image",dst);
    //imshow("matches", img_matches);
    waitKey(0);

    return 0;
}

我的目标是比较两个不同图像的两个不同部分。使用

后，您可以运行上面的代码

 g++  above_code.cpp   -o bincode   -I /usr/include/  `pkg-config --libs --cflags opencv`
./bincode image1.png image2.png

似乎我将一个矩形区域传递给关键点检测器，因此keypoints1以相对于151,115的坐标保存。

所以，我应该将一个蒙面图像传递给关键点检测器。如何创建一个填充零（或255）但矩形区域为151,115的矩阵从img1复制？

感谢。

Answer 1

以下内容根据蒙版将源图像复制到目标图像。

Mat src = imread("source.jpg",-1),dst,mask;

Rect rect(151, 115, 42, 27);

mask = Mat::zeros(src.Size(),CV_8UC1);

rectangle(mask, Point(rect.x,rect.y),Point(rect.x+rect.width,rect.y+rect.height),Scalar(255),-1);

src.copyTo(dst,mask);

虽然有更好的解决方法，但您可以将关键点转换为原始图像的大小。

如何在opencv中创建蒙版图像

1 个答案: