Could anyone help me with extracting similar features( to be used as corresponding points)in two images which need to be registered together?
2 次查看(过去 30 天)
显示 更早的评论
Hello all, I am trying to register the two attached images together, for this purpose I need corresponding similar points in the two images. For extracting such points, I tried to use connected components, regionprops, imfill, imclose functions but I couldn't get similar features. Could you please guide me if you have ideas about this problem. Thanks so much.
4 个评论
Anton Semechko
2018-7-6
OK, so the reason you want to do point-based registration is because you have been asked to do so. In my opinion, it will be much easier to align these images using an intensity-based registration approach. It will also be much easier to identify corresponding point sets in the images after they have been aligned.
采纳的回答
Anton Semechko
2018-7-8
编辑:Anton Semechko
2018-7-8
Hey, Poupack,
here is link to a function ('pairwise_histology_registration.m') that performs point-based registration of two histology images. This function detects corresponding point sets in the images using SURFs ( Speed Up Robust Features ). You can find additional info on these and other features implemented in the Computer Vision System Toolbox here.
A quick demo using your sample images:
% Sample histology images
im1=imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/124273/1.jpg');
im2=imread('https://www.mathworks.com/matlabcentral/answers/uploaded_files/124274/2.jpg');
% Register im2 to im1 using 'pairwise_histology_registration' function.
% In medical image processing jargon, im1 is called a reference image, and
% im2 a source image. Whether im1 or im2 is designated as a reference is
% not important. See function documentation for additional info.
[im_reg,T,RMSE,SD]=pairwise_histology_registration(im1,im2);
In this example, a total of 1351 corresponding point pairs were detected and aligned with accuracy of 0.5 pixels using a rigid transformation model; top 200 strongest matches shown in green. The function also supports similarity and affine transformation models. All relevant info about corresponding point sets detected by the function is contained in the structure represented by the 'SD' variable.
---
reference image
---
source image
---
source registered to reference
4 个评论
更多回答(1 个)
另请参阅
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!