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Connected components

Prerequisites

Before starting this lesson, you should be familiar with:

Learning Objectives

After completing this lesson, learners should be able to:
  • TODO

Motivation

Very often, one wants to detect objects or specific regions in images. After connected_components, the image is divided in background and foreground pixels. The next step is a connected components analysis, where spatially connected regions of foreground pixels are assigned as being part of one region.

Concept

graph TD BI("Binary image") --> CC("Connected component analysis") CC --> LI("Label image") LI --> PV("Integer pixel values") PV --> BG("0: Background") PV --> R1("1: Region 1") PV --> R2("2: Region 2") PV --> R3("...")
Connected component analysis

Activity

Open a binary image and conduct a connected components analysis.

Show activity for:

ImageJ GUI

  • Open image: xy_8bit_binary__nuclei.tif
  • Perform connected components analysis
  • Explore multi-color LUTs for object labelling
  • Explore removing and joining labels

KNIME

Connected components

Formative assessment

Fill in the blanks, using these words: less, more, 8, 255, 4, more.

  1. In 3D, pixels have ___ neighbors than in 2D. 1. 8-connected connectivity results in ___ objects than 4-connected connectivity. 1. In 3D, pixels have __ non-diagonal neighbors. 1. In 2D, pixels have __ non-diagonal neighbors. 1. A 8-bit label image can maximally have ___ objects. 1. The maximum value in a label image is equal to or ___ than the number of objects.

Follow-up material

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