Commit acc4f3eb by Christian Tischer Committed by Aliaksandr Halavatyi

### Connected components

parent 714ff3d0
 * Open image: xy_8bit_binary__nuclei.tif * Perform connected components analysis * Explore multi-color LUTs for object labelling * Explore removing and joining labels
 --- title: Connected components layout: page layout: module prerequisites: - "[Image binarization](binarization)" objectives: - 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_map: > 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("...") figure: /figures/connected_components.png figure_legend: Connected component analysis activity_preface: > Open a binary image and conduct a connected components analysis. activities: "ImageJ GUI": "connected_components/activities/connected_components_imagejgui.md" # "MATLAB": "" exercises_preface: > 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. exercises: learn_next: - "[Split touching objects](object_splitting)" - "[Measure object shapes](measure_shapes)" external_links: - "[Wikipedia: Connected components labeling](https://en.wikipedia.org/wiki/Connected-component_labeling)" --- ## Connected components analysis ### Activity: 2D connected components analysis * Open image: xy_8bit_binary__nuclei.tif * Perform connected components analysis * Explore multi-color LUTs for object labelling * Explore removing and joining labels ### Activity: 3D connected components analysis Repeat above activity but use a 3D image: * Open image: xyz_8bit_binary__spots.tif ### Formative assessment Fill in the blanks, using these words: less, more, 8, 255, 4, more. 1. In 3D, pixels have _____ neighbors than in 2D. 2. 8-connected connectivity results in _____ objects than 4-connected connectivity. 3. In 3D, pixels have ____ non-diagonal neighbors. 4. In 2D, pixels have ____ non-diagonal neighbors. 5. A 8-bit label image can maximally have _____ objects. 6. The maximum value in a label image is equal to or _____ than the number of objects. ## Learn next - shape_measurements.md
 --- title: layout: prerequisites: - "[some text](module)" objectives: - some text motivation: > some text concept_map: > graph TD BI("Binary image") --> CC("Connected component analysis") CC --> LI("Label image") figure: /figures/this_module.png figure_legend: Connected component analysis activity_preface: > activities: # "ImageJ GUI": "this_module/activities/this_module_ijgui.md" # "ImageJ Macro": "this_module/activities/this_module_ijmacro.md" # "Jython": "this_module/activities/this_module_jython.md" # "MATLAB": "this_module/activities/this_module_matlab.md" exercises_preface: > exercises: # "ImageJ GUI": "this_module/exercises/this_module_imagejgui.md" # "ImageJ Macro": "this_module/exercises/this_module_imagejmacro.md" # "Jython": "this_module/exercises/this_module_jython.md" # "MATLAB": "this_module/exercises/this_module_matlab.md" learn_next: - "[some text](module)" external_links: ---
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