Welcome to the Open Image Analysis Group
Collaboration of experts for image-based plant phenotyping, machine learning and statistical data post-processing :-)Members
- Dr. Christian Klukas (LemnaTec)
- Jean-Michel Pape (IPK Gatersleben)
- Dijun Chen (University Potsdam)
Projects
IAP - Integrated Analysis Platform
The Integrated Analysis Platform (IAP) has been designed and developed to support the analysis of large-scale image data sets of different camera systems. It aims in bridging different data domains and in integrating different approaches to data analysis and post-processing.
MCCCS - Multi Channel Classification and Clustering System
It is a generalized, script-based classification system for processing various kinds of image data. Due to the modular design, individual processing-components can be easily adapted, extended or exchanged by other external commands.
ICCS - Image Color Correction System
ICCS provides tools and methods for image color correction based on a color chart. This includes the color chart detection and several methods for image color correation using machine learning approaches.
Publications
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C. Klukas, J.-M. Pape, D. Chen: Integrated Analysis Platform: An Open-Source Information System for High-Throughput Plant Phenotyping. Plant Physiology, 165 (2014) |
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J.-M. Pape, C. Klukas: 3-D histogram-based segmentation and leaf detection for rosette plants. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T (Eds.): Computer Vision - ECCV 2014 Workshops: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, proceedings, part IV (Series: Lecture Notes in Computer Science) Cham: Springer (2015) |
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J.-M. Pape, C. Klukas: Utilizing machine learning approaches to improve the prediction of leaf counts and individual leaf segmentation of rosette plant images. Workshop: Computer Vision Problems in Plant Phenotyping (CVPPP) at BMVC (Brith Machine Vision Conference), BMVC Press (2015) |