Chaiwoot BoonyasiriwatNovember 9, 2020

Image Segmentation

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▪ Image segmentation is a task to distinguish the features

(objects or structures) or the foreground from the

background in an image.

▪ Here we concentrate on two approaches: thresholding

and boundary-based segmentation.

Image Segmentation

Russ and Neal (2016, p. 381)

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▪ Selecting features in a scene can be accomplished by

thresholding brightness values. The resulting image is a

binary or two-level image.

▪ Threshold values may be set based on the histogram.

Brightness Thresholding

Russ and Neal (2016, p. 381-382)

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Histogram can be interpreted as a sum of 3 Gaussian

peaks representing R, G, and B to colorize an image.

Colorizing an Image

Russ and Neal (2016, p. 384)

MRI image

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Thresholding of Multiband Images

Russ and Neal (2016, p. 394)

Original image Pixel color values plotted

in biconic HSI space

Resulting binary

image

Selection of HS values

for green candy

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Image Histogram in Various Spaces

Russ and Neal (2016, p. 395)

RGB Cylindrical HSI Spherical L*a*b*

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▪ Texture can be used for image segmentation.

▪ Below is an image containing 5 regions with different

texture. The brightness of pixels in each region has a

different probability distribution.

Thresholding from Texture

Russ and Neal (2016, p. 400)

Probability distribution of pixel

brightness in each region

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(a) Result of applying a variance operator with 4-pixel radius.

(b) Histogram showing that each region has a distinct

brightness.

(c) Each region can be selected by thresholding the histogram

Thresholding from Texture

Russ and Neal (2016, p. 401)

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Multiple Thresholding Criteria

Russ and Neal (2016, p. 402)

Original image Texture image using variance Intensity image

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K-Mean Clustering

Russ and Neal (2016, p. 424)

Original 3 arbitrary center

locations assigned

Resulting labels

for the current

centers

The centroids of

the regions are

assigned as the

new centers.

Regions are

redefined and

labeled.

Repeat the

process

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Region-Growing Methods

https://en.wikipedia.org/wiki/Image_segmentation#Clustering_methods

▪ Assign a set of seeds that marks the objects to be selected.

▪ The pixel with the smallest difference between its intensity

value and a region’s mean is assigned to the region.

▪ The process continues until all pixels are assigned.

▪ J. C. Russ and F. B. Neal, 2016, The Image Processing

Handbook, 7th edition, CRC Press.

References