A two-step registration-classification approach to automated segmentation of multimodal images for high-throughput greenhouse plant phenotyping

A two-step registration-classification approach to automated segmentation of multimodal images for high-throughput greenhouse plant phenotyping

Abstract Background Automated segmentation of large amount of image data is one of the major bottlenecks in high-throughput plant phenotyping. Dynamic optical appearance of developing plants, inhomogeneous scene illumination, shadows and reflections in plant and background regions complicate automat...

Full description

Bibliographic Details
Main Authors: Michael Henke, Astrid Junker, Kerstin Neumann, Thomas Altmann, Evgeny Gladilin
Format: Article
Language:English
Published: BMC 2020-07-01
Series:Plant Methods
Subjects:
Greenhouse plant phenotyping
Visible light imaging
Fluorescence imaging
Multimodal image alignment
Supervised image segmentation
Machine learning
Online Access:http://link.springer.com/article/10.1186/s13007-020-00637-x

Internet

http://link.springer.com/article/10.1186/s13007-020-00637-x

Similar Items