image-stitching

I have found some basic working examples on stitching via OpenCV for panoramic images. I have also found some useful documentation in the API docs , but I can't find out how to speed up the processing by providing additional information. In my case, I generate a set of images in a 20x20 grid of individual frames, for a total of 400 images to be stitched into a single large one. This takes an enormous amount of time on a modern PC, so it would likely take hours on a developer board. Is there any way to tell the OpenCV instance information about the images, such as me knowing in advance the

I'm a beginner programmer and just started using OpenCV. I want to stitch together 2 images using OpenCV's stitching.cpp Sample program When I attempt to stitch the images, I either get a "Can't stitch images, error code = 1" or the images come out with a lot of black blank space. I've tried to create as much overlap as I can when taking the photos, and still that's the case. Is there something wrong with the way I'm taking photos? Here are examples of pictures that I took myself and their output: Input images: Output image: This is a bad output. Notice the black space and how the image looks

I am trying to stitch a large number of images which have good amount overlap like these: ExampleImage1 and ExampleImage2 . Firstly, i want a 1D line of a grass patch. Something like this: Result . This is a screenshot of the original result, the original picture is more than 2MB. Hence couldnt upload it. This was achieved by breaking down 300 images into small sets and stitching them. Like this example but in a larger scale with more heirarchies - 0.jpg,1.jpg,2.jpg images in stitch1.jpg, 2,3,4 in stitch2.jpg and later stitching stitch1.jpg and stitch2.jpg together Now i want to get the same

To be precise, I'm attempting to run this excellent project: https://github.com/ppwwyyxx/panorama I'm using a modern mac. The issue is that I can't seem to get my computer to properly include the MTL library. I'm stuck with the endless error of: $ make [cc] matrix.cc ... matrix.cc:5:10: fatal error: 'boost/numeric/mtl/mtl.hpp' file not found #include <boost/numeric/mtl/mtl.hpp> ^ 1 error generated. make: *** [obj/matrix.o] Error 1 I've tried cmake. I've downloaded both the boost and mtl4 libraries. I've put them in my /usr/local/include directory. Nothing seems to be working. Any advice would

I'm trying to stitch two images together, using the OpenCV Java API. However, I get the wrong output and I cannot work out the problem. I use the following steps: 1. detect features 2. extract features 3. match features. 4. find homography 5. find perspective transform 6. warp perspective 7. 'stitch' the 2 images, into a combined image. but somewhere I'm going wrong. I think it's the way I'm combing the 2 images, but I'm not sure. I get 214 good feature matches between the 2 images, but cannot stitch them? public class ImageStitching { static Mat image1; static Mat image2; static

I found very useful example from images stitching but my problem was those type of images here is an exemple and here is an other image when i use opencv stitcher the reult imaages is getting smaller like this one is there any method to apply a transform into the input images so they will be like this one here is the code #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include<opencv2/opencv.hpp> #include <opencv2/features2d/features2d.hpp> #include <opencv2/nonfree/nonfree.hpp> #include <opencv2/stitching/stitcher.hpp> #include<vector> using namespace cv; using

Thanks in large part to some great answers on stackoverflow ( here , here , and here ) I've been having some pretty good success in aligning images. There is one issue, though, as you can see below. As I stitch many images together, they get smaller and smaller. My theory on why this is going on is that the camera wasn't exactly perpendicular to the ground, so as I added more and more images the natural perspective in having a camera not perpendicular to the ground caused the far images to become smaller. This could very well be completely incorrect, though. However, even when I transform the