The KNIME Image Processing Extension adds new nodes to KNIME (www.knime.org) to e.g. read more than 100 different kinds of images (thanks to the Bio-Formats API), apply well known methods for the preprocessing and to perform image segmentation and classification. Most of the included nodes operate on multi-dimensional image data (e.g. videos, 3D images, multi-channel images or even a combination of them), which is made possible by the internally used ImgLib2-API. In addition several nodes are included to calculate image features (e.g. zernike-, texture- or histogram features) for segmented images (e.g. a single cell). These feature vectors can then be used to apply machine learning methods in order to train and apply a classifier.
The KNIME Image Processing Extension currently provides about 90 nodes for (pre)-processing, filtering, segmentation, feature extraction, various views, ....
- org.knime.knip.core: Logic/Algorithms/DataStructures/Views independent of KNIME
- org.knime.knip.base: KNIME Image Processing Nodes wrapping core and providing dedicated KNIME Image Processing functionality (NodeModels etc).
- org.knime.knip.testing: KNIME Image Processing Testings nodes, e.g. for regressions tests.
- org.knime.knip.io: Image Reader/Image Writer for KNIME Image Processing.
- org.knime.knip.scijava: SciJava Libraries used by several projects
- org.knime.knip.scifio: Scifio Librarires used by several projects
- org.knime.knip.exampleplugin: Easy example plugin to get an idea how we develop nodes for KNIME.
- org.knime.knip.tracking: TrackMate Tracking integration. More soon...
You have to use the KNIME Development Kit to develop plugins for KNIME Image Processing
- Download current version of KNIME Development Kit (http://www.knime.org/downloads/overview)
- Clone Repository using your favourite Git-Client
- Eclipse: File -> Import -> Existing Projects Into Workspace
- Start KNIME as Eclipse Application out of the KNIME Development Kit (for details see http://tech.knime.org/developers) or simply write us an email.