Cris’s Image Analysis Blog

I’m pleased to announce that a new version of DIPimage has been released. There’s some performance improvements, some bug fixes, and some new functions. The measure function has some new features also, that use the convex hull of the objects. The Feret measure is computed differently now, also using the convex hull. This makes this computation more accurate and also somewhat faster.

But most importantly, we have rewritten a lot of the code that does binary arithmetic and logic operators. Binary here means these operators take two inputs. +, -, *, &, > and == are examples of binary operators. All of these used to be computed using MATLAB code, which required some nifty tricks. For example, computations between images of different type (i.e. an 8-bit integer image added to an 16-bit integer image) used to require data conversion because MATLAB cannot perform such a computation. All of these binary operators are now computed by DIPlib instead. This makes some cases much more efficient. We parallelized the arithmetic and logic code in DIPlib for further speed improvements.

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A new version of DIPimage and DIPlib has been released. You can get it at the the DIPlib website. This version fixes some bugs, adds compatibility for newer versions of MATLAB, and adds a few new functions. One interesting addition is that the function readim now will look for and use the Bio-Formats library if you install it. This means that a whole host of new image file formats are now readable. The Bio-Formats library is an open-source package created at the Laboratory for Optical and Computational Instrumentation (LOCI), University of Wisconsin-Madison. Unfortunately, their license doesn’t allow us to bundle the library with DIPimage. It is perfectly legal, however, for you to download and use the library.

In this post I want to show how to enable to DIPimage GUI to work with a new data type. In a previous post we developed a new class, dip_snake, for use with the function snakeminimize. The fully developed version of snakeminimize, which you can download here, integrates with the DIPimage GUI and uses DIPimage’s built-in automatic parameter parsing. We actually need to do something to DIPimage to get all that to work, because the dip_snake class is unknown to DIPimage. This post explains how to teach DIPimage about a new parameter type.
Note: This post is meant as a tutorial for people developing DIPimage applications, and contains nothing of interest to anybody else. If you’re not developing for DIPimage, you might want to look here instead.

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In the previous post I showed how to implement active contours (a snake). I included the link to a set of files with a complete snake implementation to plug into DIPimage. This implementations uses a class called dip_snake. In this post I wanted to show how this class is defined using MATLAB’s new 1-file-style of class definitions. Well, “new” is not completely accurate, this feature has been around for a few releases already, but I’m slow to adapt… You’ll also learn how to make a class whose objects automatically create or update a figure window, much like an object of type dip_image does.

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In this post I want to show how easy it is to implement snakes using MATLAB and DIPimage. The next release of DIPimage will have some functionality implementing snakes, and this post is based on code written for that. The first implementation of snakes I made for DIPimage used a custom class, dip_snake, to simplify usage. We decided eventually to do without the class. The code discussed here uses that first implementation, which you can download here. The most important bits of the code are identical to that in the next release of DIPimage, but the wrapping is not. Adding the class is a nice excuse to show how to modify DIPimage to understand a new parameter type. I will discuss that in a future post.

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