Image Processing Applications

Segmentation of cells using the Watershed algorithm.

This tutorial workflow shows how you can visually inspect your data using KNIME's Hilite mechanism.

Illustrates how differently median and average filters perform on salt-and-pepper-noisy images.

This workflow shows how to find the nearest neighbor of each label within an image segmentation using the Similarity Search Node of the KNIME Distance Matrix Extension.

This workflow shows how to calculate the distances between a selected label/region of intereset ("roi") and all the other rois within a image segmentation. Here, Euclidean distance is used but can be replaced by any other coordinate-based distance metric.

This wokflow shows how to determine the number of cells contained in an image.

This workflow shows how you can measure an object's length in y-dimension f(x) for each x-value it spans. This can, of course, be generalized for measuring in any dimension.
The workflow also calculates the change of length as a backward difference f(x) - f(x-1).

This tutorial introduces an image enhancement algorithm that substracts a blurred version of an image from a lower blurred version of the original image to emphasize edges and details in images.

This tutorial introduces an image enhancement algorithm that substracts a blurred version of an image from a lower blurred version of the original image to emphasize edges and details in images.

This tutorial introduces an image enhancement algorithm that substracts a blurred version of an image from a lower blurred version of the original image to emphasize edges and details in images.