OpenCV:如何使用mask参数进行特征点检测(SURF)

OpenCV: howto use mask parameter for feature point detection (SURF)

本文关键字：特征 检测 SURF 何使用 mask 参数 OpenCV      更新时间：2023-10-16

我想限制一个surfffeaturedetector到一组区域(掩码)。对于一个测试，我只定义了一个掩码:

Mat srcImage; //RGB source image
Mat mask = Mat::zeros(srcImage.size(), srcImage.type());
Mat roi(mask, cv::Rect(10,10,100,100));
roi = Scalar(255, 255, 255);
SurfFeatureDetector detector();
std::vector<KeyPoint> keypoints;
detector.detect(srcImage, keypoints, roi); // crash
//detector.detect(srcImage, keypoints); // does not crash

当我传递"roi"作为掩码时，我得到这个错误:

OpenCV Error: Assertion failed (mask.empty() || (mask.type() == CV_8UC1 && mask.size() == image.size())) in detect, file /Users/ux/Downloads/OpenCV-iOS/OpenCV-iOS/../opencv-svn/modules/features2d/src/detectors.cpp, line 63

这是怎么回事?我怎样才能正确地传递一个掩码到SurfFeatureDetector的"检测"方法?

认为,

关于遮罩的两件事

  • 掩码应该是一个8位无符号字符的1通道矩阵，转换为openv类型CV_8U。在您的情况下，掩码类型为srcImage.type()，这是一个3通道矩阵
  • 你正在传递roi到检测器，但你应该传递mask。当您更改roi时，您也更改了mask。

Mat srcImage; //RGB source image
Mat mask = Mat::zeros(srcImage.size(), CV_8U);  // type of mask is CV_8U
// roi is a sub-image of mask specified by cv::Rect object
Mat roi(mask, cv::Rect(10,10,100,100));
// we set elements in roi region of the mask to 255 
roi = Scalar(255);  
SurfFeatureDetector detector();
std::vector<KeyPoint> keypoints;
detector.detect(srcImage, keypoints, mask);     // passing `mask` as a parameter

我将您的ROI代码添加到我正在处理的一些现有代码上，通过以下更改，它对我有效

cv::Mat mask = cv::Mat::zeros(frame.size(), CV_8UC1);  //NOTE: using the type explicitly
cv::Mat roi(mask, cv::Rect(10,10,100,100));
roi = cv::Scalar(255, 255, 255);
//SURF feature detection
const int minHessian = 400;
cv::SurfFeatureDetector detector(minHessian);
std::vector<cv::KeyPoint> keypoints;
detector.detect(frame, keypoints, mask);              //NOTE: using mask here, NOT roi
cv::Mat img_keypoints; 
drawKeypoints(frame, keypoints, img_keypoints, cv::Scalar::all(-1), cv::DrawMatchesFlags::DEFAULT);
cv::imshow("input image + Keypoints", img_keypoints);
cv::waitKey(0);

如果不改变类型和使用mask而不是roi作为掩码，我也会得到一个运行时错误。这是有道理的，因为检测方法需要一个蒙版——它应该与原始图像的大小相同，而roi不是(它是一个100x100的矩形)。要直观地看到这一点，请尝试显示掩码和roi

cv::imshow("Mask", mask);
cv::waitKey(0);
cv::imshow("ROI", roi);
cv::waitKey(0);

类型必须匹配also;遮罩应该是单通道，而您的图像类型可能是类型16，它映射到CV_8UC3，一个三通道图像

如果你想对不规则蒙版应用相同的方法，那么:

Mat& obtainIregularROI(Mat& origImag, Point2f topLeft, Point2f topRight, Point2f botLeft, Point2f botRight){
        static Mat black(origImag.rows, origImag.cols, origImag.type(), cv::Scalar::all(0));
        Mat mask(origImag.rows, origImag.cols, CV_8UC1, cv::Scalar(0));
        vector< vector<Point> >  co_ordinates;
        co_ordinates.push_back(vector<Point>());
        co_ordinates[0].push_back(topLeft);
        co_ordinates[0].push_back(botLeft);
        co_ordinates[0].push_back(botRight);
        co_ordinates[0].push_back(topRight);
        drawContours( mask,co_ordinates,0, Scalar(255),CV_FILLED, 8 );
       // origImag.copyTo(black,mask);
        //BasicAlgo::getInstance()->writeImage(black);
        return mask;  // returning the mask only
    }

然后像往常一样，生成SIFT/SURF/…指针

//为SIFT特征检测器创建智能指针

Ptr<FeatureDetector> SIFT_FeatureDetector = FeatureDetector::create("SIFT");
vector<KeyPoint> SIFT_Keypoints;
vector<KeyPoint> SIFT_KeypointsRotated; 
Mat maskedImg = ImageDeformationOperations::getInstance()->obtainIregularROI( rotatedImg,rotTopLeft,rotTopRight,rotBotLeft,rotBotRight);
SIFT_FeatureDetector->detect(rotatedImg, SIFT_KeypointsRotated, maskedImg);
Mat outputSIFTKeyPt;
drawKeypoints(rotatedImg, SIFT_KeypointsRotated, outputSIFTKeyPt, keypointColor, DrawMatchesFlags::DEFAULT);
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