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Summary and next steps

A summary of week 1 of the Introduction to image analysis for plant phenotyping

So far in the course we have covered the following:

  • What is image analysis, and how can we use image data?
  • The challenges of image analysis using plant data
  • An introduction to some of the typical image analysis problems in plant phenotyping that we’ll look at in more detail later in the course
  • These problems include object detection, segmentation, counting objects and the use of multiple image data sets
  • How digital image data is structured : Pixels with Red, Green and Blue channels or grayscale values
  • How to optimise the settings on your camera to capture quality experimental images
  • These settings include focus, aperture, exposure time and sensor sensitivity (ISO value)
  • Lossless (e.g. PNG format) versus lossy compression (e.g. JPG format)
  • The difference between 8-bit and 16-bit images

In the material next week we’ll look a bit more at how to put some of these ideas into practice. This will involve the use of software tools such as Fiji and Python. In particular we will look in detail at a common image analysis technique, image thresholding.

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Introduction to Image Analysis for Plant Phenotyping

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FutureLearn - Learning For Life

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