emgucv

What is the fastest way to get number of white pixels in a binary picture using OpenCV? Is there something faster than using two for loops and accessing the image pixel by pixel? The most succinct way to accomplish this is: cv::Mat image, mask; //image is CV_8UC1 cv::inRange(image, 255, 255, mask); int count = cv::countNonZero(mask); If you are operating on a binary image, then the call to cv::inRange() is unnecessary, and simply cv::countNonZero() will suffice. Although any method must iterate through all the pixels, this may be able to harness OpenCV's built-in parallel_for_() , which allows

I have byte array with yuv420 data. byte[] yuv420;//yuv data How can I convert this to an Image<Bgr, byte> ? I found a math formula to convert to RGB and then to Image<Bgr, byte> but it is very slow. Is there a way to convert it faster? There is a class in Emgu for converting COLOR_CONVERSION(enum CV_YUV2RGB Convert YUV color to RGB) but I can not understand how use this class. Can anyone help? static Bitmap ConvertYUV2RGB(byte[] yuvFrame, byte[] rgbFrame, int width, int height) { int uIndex = width * height; int vIndex = uIndex + ((width * height) >> 2); int gIndex = width * height; int

I need to find the coordinates of three black squares in the test form. I took the example code from the site emgu.com and slightly changed it, but he does not find what I need. The size of image is A4, and the size of the test form is A5. I am hope for your help :) I nearly forgot, the size of squares 30 pixels. private void DetectRectangles(Image<Gray, byte> img) { var size = new Size(3, 3); CvInvoke.GaussianBlur(img, img, size, 0); CvInvoke.AdaptiveThreshold(img, img, 255, AdaptiveThresholdType.MeanC, ThresholdType.Binary, 75, 100); UMat cannyEdges = new UMat(); CvInvoke.Canny(img,

I'm using Emgu.CV to perform some basic image manipulation and composition. My images are loaded as Image<Bgra,Byte> . Question #1: When I use the Image<,>.Add() method, the images are always blended together, regardless of the alpha value. Instead I'd like them to be composited one atop the other, and use the included alpha channel to determine how the images should be blended. So if I call image1.Add(image2) any fully opaque pixels in image2 would completely cover the pixels from image1, while semi-transparent pixels would be blended based on the alpha value. Here's what I'm trying to do in

I have already done the comparison of 2 images of same scene which are taken by one camera with different view angles(say left and right) using SURF in emgucv (C#). And it gave me a 3x3 homography matrix for 2D transformation. But now I want to make those 2 images in 3D environment (using DirectX). To do that I need to calculate relative location and orientation of 2nd image(right) to the 1st image(left) in 3D form. How can I calculate Rotation and Translate matrices for 2nd image? I need also z value for 2nd image. I read something called 'Homograhy decomposition'. Is it the way? Is there