plugin

Image segmentation based on the MOSAIC Discrete region competition algorithm. 

Easy-to-use, computationally efficient, two- and three-dimensional, feature point-tracking tool for the automated detection and analysis of particle trajectories as recorded by video imaging in cell biology. 

The tracking process requires no apriori mathematical modelling of the motion, it is self-initialising, it discriminates spurious detections, and it can handle temporary occlusion as well as particle appearance and disappearance from the image region. 

The plugin is well suited for video imaging in cell biology relying on low-intensity fluorescence microscopy. It allows the user to visualize and analyze the detected particles and found trajectories in various ways:

• Preview and save detected particles for separate analysis
• Global non progressive view on all trajectories
• Focused progressive view on individually selected trajectory
• Focused progressive view on trajectories in an area of interest

It also allows the user to find trajectories from uploaded particles position and information text files and then to plot particles parameters vs. time - along a trajectory

This ImageJ plugin creates high resolution PSF images by averaging many bead im- ages as well as exploiting the assumption that the point spread function is rotationally symmetric with respect to the axial axis (z-direction).

OMERO.webtagging is the umbrella name for tools developed to enhance use of text annotations (tags) in OMERO. There are two tools at present, autotag and tagsearch.

This plugin can be used for inferring spatial interactions between patterns of spot-like objects in images or between coordinates read from a file. 

This plugin can be used to add synthetic Poisson-distributed noise to an image in order to simulate shot noise of various signal-to-noise ratios. It can be used to generate benchmark images in order to assess the accuracy and robustness of image processing algorithms as a function of the noise level present in images.

Histogram-based background subtractor for ImageJ.

The implemented algorithm is based on the assumption that, compared to the background region, object (foreground) regions are small. The plugin builds local histograms and assumes the most occuring intensity to be part of the background.

EnhanceEdges enhances or identifies edges in an image, which can improve object identification or other downstream image processing.