feature-detection

问题 I need to find and match feature points in stereo images. Therefore I want to compare the different Feature Detection algorithms that are supported in OpenCV 2.4.5. by passing "SURF", "SIFT", etc. to the function. The code snippet: #include "opencv2/opencv.hpp" #include <opencv/highgui.h> #include <opencv2/nonfree/features2d.hpp> using namespace cv; using namespace std; ... void DisparityAnalysis::detectKeyPoints(Mat1b leftImageGrey, Mat1b rightImageGrey, string algorithmName) { Ptr

问题 The question is about feature detection concept. I'm stuck after I finding the corner of image and I want to know how to finding the feature point within the computed corners. Suppose I have grayscale image that have data like this A = [ 1 1 1 1 1 1 1 1; 1 3 3 3 1 1 4 1; 1 3 5 3 1 4 4 4; 1 3 3 3 1 4 4 4; 1 1 1 1 1 4 6 4; 1 1 1 1 1 4 4 4] if I use B = imregionalmax(A); the result would be like this B = [ 0 0 0 0 0 0 0 0; 0 1 1 1 0 0 1 0; 0 1 1 1 0 1 1 1; 0 1 1 1 0 1 1 1; 0 0 0 0 0 1 1 1; 0 0 0

问题 I have a training set of images, for each of which I've detected and computed their feature vectors (using ORB feature descriptors and extractors. The questions is : since I need to save those features to reutilise them for matching against test images (using SVM classifier); what is the best way to store the feature vectors, locally on the Android device? The feature vectors to be saved are of variable size per image, and are thus those with non-maximal sizes are padded with zeros to unify

问题 For my college project I need to identify a species of a plant from plant leaf shape by detecting edges of a leaf. (I use OpenCV 2.4.9 and C++), but the source image has taken in the real environment of the plant and has more than one leaf. See the below example image. So here I need to extract the edge pattern of just one leaf to process further. Using Canny Edge Detector I can identify edges of the whole image. But I don't know how to proceed from here to extract edge pattern of just one

问题 I am using the following algorithm to detect skin color, but its not working real well in different lighting conditions. Can anybody offer any advice how to improve it or suggest a better approach R > 95 AND G > 40 AND B > 20 AND max{R, G, B} – min{R, G, B} >15 AND |R – G| > 15 AND R > G AND R > B OR R > 220 AND G > 210 AND B > 170 AND |R – G| <= 15 AND R > B AND G > B http://softexpert.wordpress.com/2007/10/17/skin-color-detection/ Cheers 回答1: Your given algorithm is simple colour based

问题 I have been trying to figure out whether it's possible to nest CSS feature queries (also known as “CSS @supports ”) and regular media queries, and what would be the correct way to do it. Example A shows the feature query inside the media query. Example B shows the media query inside the feature query. Is it even possible to nest them at all? If so, is there a preferred nesting style? A or B? .foo { background: red; } /* EXAMPLE A */ @media (min-width: 50em) { .foo { background: green; }

问题 I have a video feed. This video feed contains several lights blinking at different rates. All lights are the same color (they are all infrared LEDs). How can I detect the position and frequency of these blinking lights? Disclaimer: I am extremely new to OpenCV. I do have a copy of Learning OpenCV , but I am finding it a bit overwhelming. If anyone could explain a solution in OpenCV terminology, it would be greatly appreciated. I am not expecting code to be written for me. 回答1: Threshold each

问题 I am using the ORB feature detector to find matches between two images using this code: FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB); DescriptorExtractor descriptor = DescriptorExtractor.create(DescriptorExtractor.ORB);; DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE_HAMMING); // First photo Imgproc.cvtColor(img1, img1, Imgproc.COLOR_RGB2GRAY); Mat descriptors1 = new Mat(); MatOfKeyPoint keypoints1 = new MatOfKeyPoint(); detector

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 5 years ago . I want to detect content of images. For example I want to use the above image as an input, and get as output list of terms like: sky, water, sea, buildings etc. Any idea how to start? 回答1: The short answer is: yes. Below is a quick first effort, using OpenCV - essentially I just

问题 My main goal is to detect the little line over the left of the image: By detecting line I mean I want a line equation of this form: y = ax + b. In order to find the line, I tried using this Hough Transform java class, which doesn't return the equation I want but at least supposed to find the line, but what happens is that it does not detect the line I want (it actually locates only the horizontal line in the image, and even this is not perfect. The y cord is located perfectly but the x is