feature-detection

问题 i'm trying to evaluate SIFT and SURF Detectors by Repeatability criteria. i find out that below method can find Repeatability ,Correspondence of SIFT and SURF cv::evaluateFeatureDetector(img_1c, img_2c, h12, &key_points_1, &key_points_2, repeatability, corrCounter); some of the result are listed below: Number Repeatibility Correspond Keypoint 1st Keypoint 2th 1to2 0.7777778 140 224 180 1to3 0.7125 114 224 161 1to4 0.704918 86 224 123 1to5 0.6853933 61 224 89 1to6 0.6521739 45 224 69 for first

问题 I want to match feature points in stereo images. I've already found and extracted the feature points with different algorithms and now I need a good matching. In this case I'm using the FAST algorithms for detection and extraction and the BruteForceMatcher for matching the feature points. The matching code: vector< vector<DMatch> > matches; //using either FLANN or BruteForce Ptr<DescriptorMatcher> matcher = DescriptorMatcher::create(algorithmName); matcher->knnMatch( descriptors_1,

问题 [EDIT] I have devised some code for image comparison. The matching part is still a bit flawed and I would love some assitance. The project can be found at - GitHub. I have these two images Img1 and Img2 : When I use the following command in openCV Mat img1 = Highgui.imread("mnt/sdcard/IMG-20121228.jpg"); Mat img2 = Highgui.imread("mnt/sdcard/IMG-20121228-1.jpg"); try{ double l2_norm = Core.norm( img1, img2 ); tv.setText(l2_norm+""); } catch(Exception e) { //image is not a duplicate } I get a

问题 I'm trying to create an android application for detecting objects from camera using openCV, I read the openCV reference and found there are many methods for image detection, my purpose is to create an application 1) App can detect the any object from database(set of objects that can be detected) on real time camera frame.(Speed of processing/detection is important) 2) The database of object images will be updated from time to time.(database preferably on an external server) - Does this mean I

问题 I am looking for an efficient way to detect the small boxes around the numbers (see images)? I already tried to use hough transformation with no success. Any ideas? I need some hints! I am using opencv... 回答1: I'd start by trying to detect the rectangular boundary of the overall sheet, then applying a perspective transform to make it truly rectangular. Crop that portion of the image out. If possible, then try to make the alternating white and grey sub-rectangles have an equal background

问题 I am building a simple project in Python3, using OpenCV3, trying to match jigsaw pieces to the "finished" jigsaw image. I have started my tests by using SIFT. I can extract the contour of the jigsaw piece and crop the image but since most of the high frequencies reside, of course, around the piece (where the piece ends and the floor starts), I want to pass a mask to the SIFT detectAndCompute() method, thus forcing the algorithm to look for the keypoints only within the piece. test_mask = np

问题 If there is a given 2d array of an image, where threshold has been done and now is in binary information. Is there any particular way to process this image to that I get multiple blob's coordinates on the image? I can't use openCV because this process needs to run simultaneously on 10+ simulated robots on a custom simulator in C. I need the blobs xy coordinates, but first I need to find those multiple blobs first. Simplest criteria of pixel group size should be enough. But I don't have any

问题 How can my JavaScript detect if an event is available? I'm aware of some great event-compatibility tables, but I need to use feature detection, not browser-sniffing plus a lookup table. Specifically, my JS makes great use of the DOM mutation events ( DOMNodeInserted and DOMSubtreeModified ) -- which work great in all browsers except (of course) Internet Explorer. So, how would I detect if a browser supports DOMNodeInserted ? 回答1: If you just want to check if the browser supports mutation

问题 Everywhere in features2D classes I see terms query and train . For example matches have trainIdx and queryIdx , and Matchers have train() method. I know the definition of words train and query in English, but I can't understand the meaning of this properties or methods. P.S. I understand, that it's very silly question, but maybe it's because English is not my native language. 回答1: To complete sansuiso's answer, I suppose the reason for choosing these names should be that in some application

问题 In my main.cpp I have an excerpt: Ptr<FastFeatureDetector> fastDetector = FastFeatureDetector::create(80, true); while (true) { Mat image = // get grayscale image 1280x720 timer.start(); detector->detect(image, keypoints); myfile << "FAST\t" << timer.end() << endl; // timer.end() is how many seconds elapsed since last timer.start() keypoints.clear(); timer.start(); for (int i = 3; i < image.rows - 3; i++) { for (int j = 3; j < image.cols - 3; j++) { if (inspectPoint(image.data, image.cols, i,