Find a new cheat sheet for using ImageJ’s Java API with methods grouped into useful categories here.
ImagingBook’s core library
imagingbook-common provides most of the functionality required by the demo ImageJ plugins that supplement each book chapter. It helps to keep the plugins slim, avoids code duplication, and makes the code easily portable to other environments.
For users who want to use
imagingbook-common in their Maven projects, the library is now (starting with release 1.5) available as a public Maven artefact. See here for further details.
Modern Java IDEs, such as Eclipse, IntelliJ or NetBeans are excellent tools for developing ImageJ plugins and should be used for projects of any size. However, beginners sometimes find it difficult to set up their IDE to work smoothly with ImageJ’s file structure. We have created a small repository on GitHub that provides a simple setup to get started with ImageJ plugin development in Eclipse or IntelliJ:
Mistakes happen and some even remain undetected for quite some time. Many careful readers have helped us to correct smaller and greater errors. This time our special thanks go to Jan Sellner for thoroughly checking through Chapter 17 (Anisotropic Diffusion Filters) of the German 3rd edition. The updated errata pages can be found here.
Today, the imagingbook source code repository was officially moved to GitHub for various technical reasons. Bitbucket has been a great host, providing free private repositories by default – thanks for this and many other great features! While we’ll continue to use Bitbucket for other projects, the main motive for this switch was the easier coupling to the static web pages we use for creating JavaDoc output. We also added a new repository for release (JAR) files that is under GIT version control.
Here is a listing of all relevant repositories:
- Source code: https://github.com/imagingbook/imagingbook-public
- JavaDoc pages: https://imagingbook.github.io/imagingbook-doc
- Release files: https://github.com/imagingbook/imagingbook-jars
Related repositories (projects using the imagingbook library):
- Camera calibration: https://github.com/imagingbook/imagingbook-calibrate
- Viola-Jones Face Detection: https://github.com/imagingbook/imagingbook-violajones
Please visit our main site imagingbook.com for additional details.
A new relase of the imagingbook-common library has been released today. This version fixes several bugs, mostly releated to the ImageAccessor and associated classes. The new JAR files can be downloaded from this location:
In the meantime the imagingbook source code repository has been moved to GitHub for technical reasons. An official announcement will follow shortly.
The color quantization code contained in the imagingbook library has been updated and enhanced (see package imagingbook.pub.color.quantize):
- KMeansClusteringQuantizer: new quantizer using k-means clustering,
- KMeansClusteringQuantizerApache: new quantizer using the Apache Commons Math k-means clustering implementation,
- MedianCutQuantizer: revised version,
- OctreeQuantizer: re-implemented and operational now.
All the above are subclasses of ColorQuantizer, which is now an abstract class (used to be an interface) and defines various common methods.
Demo ImageJ plugins are provided for the above classes in the imagingbook-plugins-all repository.
- The code repository is now GIT-based (SVN before) and has moved from SourceForge to Bitbucket:
- The old SourceForge repo still exists but holds no current code and will be retired sooner or later.
- The entire code was “mavenized” and structured according to Maven standards. It will be deployed at a central repository manager (with POM dependencies) in the near future.
- JAR files for plugins and the imagingbook common library have been renamed for better consistency.
- JavaDoc information has been added to all plugin collections. JavaDocs now also link to the underlying Java source code.
We are pleased to announce that the much-anticipated 2nd English edition (2016) of our “professional” book series will be shortly available. The new edition was completely revised and expanded with new content and improved teaching material and has significantly grown in volume to over 800 pages. It contains new chapters on automatic thresholding, filters and edge detection for color images, edge-preserving smoothing filters, non-rigid image matching, and Fourier shape descriptors. Updated Java/ImageJ source code with new chapter materials is available on SourceForge.
NEW: Digital Image Processing — An Algorithmic Introduction Using Java
by W. Burger and M.J. Burge, 2nd edition, Springer London (2016)
ISBN: 978-1-4471-6683-2 (Hardcover), 978-1-4471-6684-9 (eBook)
Find at: Springer | Amazon.com | Amazon.uk | Amazon.de
Download: Table of contents [PDF]
Auch bei der neuesten deutschen Ausgabe ging es (wie immer) nicht ganz ohne Fehler ab. Neben kleineren Typos finden sich im Text leider auch ein paar inhaltlich wichtige Fehler — die zugehörigen Korrekturen sind HIER (German, 3rd edition) zusammengefasst. Vielen Dank an unsere Leser für ihre Rückmeldungen!