Semi-automated Shoot Image Segmentation using k-means Clusering of Eigen-colors - kmSeg v0.2

Introduction

kmSeg tool was developed to enable efficient supervised segmentation and basic phenotyping of plant shoots in RGB images as well as grayscale intensity images.

Key Features

The kmSeg tool automatically clusters image colors into a small predefined number of classes (typically between 10 and 25) that are in the next step manually assigned to either plant or non-plant (background) categories. A number of phenotypic traits of the overall geometry and colors of segmented plant shoots is generated for every and all images in the selected folder. The full list and descriptions of phenotypic traits calculated with kmSeg can be found in the kmSeg quick guide (3MB).

Downloads

Download kmSeg for Windows x64 (50MB)

Download kmSeg for Linux (50MB)

By downloading, installing and/or using this software the user agrees with the following license conditions.

This software requires MATLAB run time libraries (2020a) to be installed:

MATLAB run time for Windows x64 (~2GB).
MATLAB run time for Linux (~2GB).

Windows users should also install the run-time components from the following link: https://www.microsoft.com/en-us/download/details.aspx?id=48145.

Some information on dependencies of the MATLAB run-time components in Linux can be found here: https://de.mathworks.com/matlabcentral/answers/358052-is-there-a-list-of-matlab-runtime-dependencies.

General hardware requirements for MATLAB applications can be found here: https://de.mathworks.com/support/requirements/matlab-system-requirements.html.
For processing of image files of the 4-8 MP size such as provided with the supplementary data, 8GB or more RAM is recommended.

Quick Start

For install notes and further informations, please see the Quick Guide.

The movie below demonstrates the application of the kmSeg tool to segmentation of a top-view arabidopsis image:
https://ag-ba.ipk-gatersleben.de/kmseg_movie.html.

References

[1] Henke M, Neumann K, Altmann T, Gladilin E. Semi-automated ground truth segmentation and phenotyping of plant structures using k-means clustering of eigen-colors (kmSeg). Agriculture 11 (2021) 1098. https://dx.doi.org/10.3390/agriculture11111098

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