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What you will cover in the course
The main topics of the course 'Introduction to image analysis for plant phenotyping'
The main topics we will cover during this six-week course are as follows:
Week 1 – an introduction to image analysis:
- What is image analysis and how is it used in plant phenotyping?
- What are digital images?
- What to consider when producing digital images
Week 2 – software tools for image analysis:
- Working with images in Fiji (ImageJ)
- Image thresholding
- An introduction to using Python
Week 3 – coding for image analysis:
- An introduction to programming with Python
- The building blocks of programming
- Morphological operations – erosion and dilation
Week 4 – common tasks in image analysis:
- Noise reduction and filtering
- Counting and labelling
- Model-based and feature-based image segmentation
Week 5 – Beyond 2D image data:
- Motion and motion detection in image analysis (video or time sequenced data)
- Volumetric data (3D data stacks)
- Hyperspectral image data
Week 6 – 3D image reconstruction and course summary:
- Why 3D? Example applications
- 3D data types
- An overview of 3D reconstruction approaches
- Discussion and conclusions
This article is from the online course:
Introduction to Image Analysis for Plant Phenotyping
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This article is from the free online
Introduction to Image Analysis for Plant Phenotyping
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