The KNIME Image Processing Extension adds new nodes to KNIME Analytics Platform to, e.g. read more than 100 different kinds of images (thanks to the Bio-Formats library), apply well-known methods for preprocessing, 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 ImgLib2. In addition, several nodes to calculate image features (e.g. zernike-, texture- or histogram features) for segmented images (e.g. a single cell) are included. These feature vectors can 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, ....

For more information how to install/use KNIME Image Processing see: https://www.knime.com/community/image-processing

Example Workflows can be found at: https://hub.knime.com/knime/spaces/Examples/latest/99_Community/01_Image_Processing/

• 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.feature: Eclipse feature for org.knime.knip.core and org.knime.knip.base
• org.knime.knip.testing: KNIME Image Processing Testing nodes, e.g. for regressions tests.
• org.knime.knip.testing.feature: Eclipse feature for KNIME Image Processing Testings nodes.
• org.knime.knip.io: Image Reader/Image Writer for KNIME Image Processing.
• org.knime.knip.update: Eclipse update site for KNIME Image Processing and depedencies.
• org.knime.knip.tracking: TrackMate Tracking integration.

See this repository for instructions.