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Image segmentation Grey scale image Binary image

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Presentation on theme: "Image segmentation Grey scale image Binary image"— Presentation transcript:

1 Image segmentation Grey scale image Binary image 34 19 12 13 18 55 21
56 11 31 14 10 15 54 33 Threshold range 20-255 1 1 1 1 1 1 1 1 1

2 But simpler to interpret:
8-bits Binary image 1-bit Labelled objects Less information But simpler to interpret: 46 objects with different properties (size, shape, intensity, …) 65536 pixels Intensity range 0-255 A lot of information !

3 Segmentation exercises
Open Samples>Blobs How to determine the threshold? Manual (use histogram and line profile for help) Automatically Remove “noise” with filters before applying segmentation

4 Edge detection Process>Find edge Open Samples>Blobs
Uses a Sobel edge detector to highlight sharp changes in intensity in the active image or selection Open Samples>Blobs Detect the edges Apply a Gaussian Filter then detect the edges

5 Color thresholding Thresholds 24-bit RGB images based on Hue Saturation and Brightness (HSB), Red Green and Blue (RGB), CIE Lab or YUV components. Great method to extract DAB signal from histological stains Image>Adjust>Color Thresholding Open Samples>Fluorescent cells Open BrdU-PCNA


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