In a recent post I demonstrated the use of bwdist (binary image Euclidean distance transform) to perform isotropic dilation. This was inspired by something that Brett asked me about. ... 더 읽어보기 >>

I often find myself writing small functions that help visualize certain image processing algorithms. For example, my last three posts on bwlabel included identical snippets of code that... 더 읽어보기 >>

Several questions I've seen about bwlabel are about finding the correspondences between object labels in two images. In other words, if a particular pixel is in the foreground in two... 더 읽어보기 >>

The three most common questions I've been hearing about bwlabel, which is used for labeling connected components in a binary image, are about Search order ... 더 읽어보기 >>

I've received several questions over the past months about the search order for the function bwlabel and whether it can be changed. Today's post discusses the search-order issue, how useful it... 더 읽어보기 >>

In a comment on my "Connected component labeling - Part 6" post, Martin Isenburg asked "what is the rationale behind the design decision to have bwlabeln work on individual pixels rather than on... 더 읽어보기 >>

I've about run out of things to say for now about connected component labeling algorithms. ("Hurray!" shouts the audience.) For reference, here's a summary of all the posts in the... 더 읽어보기 >>

I described in my previous connected component labeling post the algorithm used by bwlabeln. This time I'll talk about the variation used by bwlabel. This variation uses run-length encoding as... 더 읽어보기 >>

In this part of the connected component labeling series, I'll finally get to one of the algorithms actually used in the Image Processing Toolbox. It's based on a technique called ... 더 읽어보기 >>

OK, I've learned an important lesson about this blog: I really shouldn't start up two topics series at the same time. It's too hard to find the time to compose posts on both topics each... 더 읽어보기 >>