C++ OpenCV：如何使用掩码参数进行特征点检测（SURF）
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OpenCV: howto use mask parameter for feature point detection (SURF)
提问by Hyndrix
I want to limit a SurfFeatureDetector to a set of regions (mask). For a test I define only a single mask:
我想将 SurfFeatureDetector 限制为一组区域（掩码）。对于测试，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
When I pass the "roi" as the mask I get this error:
当我将“roi”作为掩码传递时，出现此错误：
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
What is wrong with this? How can I correctly pass a mask to the SurfFeatureDetector's "detect" method?
这有什么问题？如何正确地将掩码传递给 SurfFeatureDetector 的“检测”方法？
Regards,
问候，
回答by Alexey
Two things about the mask.
关于面具的两件事。
- the mask should be a 1-channel matrix of 8-bit unsigned chars, which translates to opencv type
CV_8U. In your case the mask is of type srcImage.type(), which is a 3-channel matrix - you are passing
roito the detector but you should be passingmask. When you are making changes toroi, you are also changingmask.
- 掩码应该是一个 8 位无符号字符的 1 通道矩阵，转换为 opencv 类型
CV_8U。在您的情况下，掩码的类型为 srcImage.type()，这是一个 3 通道矩阵 - 您正在通过
roi检测器，但您应该通过mask。当您对 进行更改时roi，您也在更改mask。
the following should work
以下应该工作
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
回答by alrikai
I tacked your ROI code onto some existing code I was working on, with the following changes it worked for me
我将您的 ROI 代码添加到我正在处理的一些现有代码上，以下更改对我有用
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);
Without the changes to the type and the use of maskinstead of roias your mask, I'd get a runtime error as well. This makes sense, as the detect method wants a mask -- it should be the same size as the original image, and roi isn't (it's a 100x100 rectangle). To see this visually, try displaying the mask and the roi
如果不更改类型和使用mask代替roi作为掩码，我也会收到运行时错误。这是有道理的，因为检测方法需要一个掩码——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);
The type has to match also; the mask should be single channel, while your image type is likely of type 16, which maps to CV_8UC3, a triple channel image
类型也必须匹配；掩码应该是单通道，而您的图像类型可能是类型 16，它映射到CV_8UC3三通道图像
回答by Spandan
If you are looking to apply the same for irregular mask then:
如果您希望将相同的方法应用于不规则蒙版，则：
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
}
Then as usual, generate SIFT/SURF/... pointer
然后像往常一样，生成 SIFT/SURF/... 指针
// Create smart pointer for SIFT feature detector.
// 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);
