Image Segmentation

Segment images

Image segmentation is the process of partitioning an image into parts or regions. This division into parts is often based on the characteristics of the pixels in the image. For example, one way to find regions in an image is to look for abrupt discontinuities in pixel values, which typically indicate edges. These edges can define regions. Other methods divide the image into regions based on color values or texture.

Apps

Color Thresholder	Threshold a color image
Image Segmenter	Segment an image by refining regions

Functions

activecontour Segment image into foreground and background using active contours (snakes)

`imsegfmm`	Binary image segmentation using Fast Marching Method
`imseggeodesic`	Segment image into two or three regions using geodesic distance-based color segmentation
`imsegkmeans`	K-means clustering based image segmentation
`imsegkmeans3`	K-means clustering based volume segmentation
`watershed`	Watershed transform
`gradientweight`	Calculate weights for image pixels based on image gradient
`graydiffweight`	Calculate weights for image pixels based on grayscale intensity difference
`grayconnected`	Select contiguous image region with similar gray values

`graythresh`	Global image threshold using Otsu's method
`multithresh`	Multilevel image thresholds using Otsu’s method
`otsuthresh`	Global histogram threshold using Otsu's method
`adaptthresh`	Adaptive image threshold using local first-order statistics

`boundarymask`	Find region boundaries of segmentation
`superpixels`	2-D superpixel oversegmentation of images
`lazysnapping`	Segment image into foreground and background using graph-based segmentation
`grabcut`	Segment image into foreground and background using iterative graph-based segmentation
`superpixels3`	3-D superpixel oversegmentation of 3-D image
`imoverlay`	Burn binary mask into 2-D image
`labeloverlay`	Overlay label matrix regions on 2-D image
`label2idx`	Convert label matrix to cell array of linear indices

`jaccard`	Jaccard similarity coefficient for image segmentation
`dice`	Sørensen-Dice similarity coefficient for image segmentation
`bfscore`	Contour matching score for image segmentation

Topics

Segmentation Using the Image Segmenter

Image Segmentation Using the Image Segmenter App

This topic provides an overview of the Image Segmenter app and its capabilities.

Segmentation Using Graph Cut in Image Segmenter

Use graph cut to segment an image into foreground and background elements, using classification lines you draw over the image.

Segmentation Using Local Graph Cut (Grabcut) in Image Segmenter

Use local graph cut (grabcut) to segment an image into foreground and background elements, using classification lines you draw over the image.

Segmentation Using Find Circles in Image Segmenter

To segment circles from an image, use the Find Circles option in Image Segmenter app and specify a range of acceptable diameters.

Segmentation Using Auto Cluster in Image Segmenter

Use the Auto Cluster option in Image Segmenter app to segment an image into foreground and background elements.

Install Sample Data Using the Add-On Explorer

Image Processing Toolbox Image Data package contains sample 3-D volumetric data.

Segmentation Using the Color Thresholder

Image Segmentation Using the Color Thresholder App

This example shows how to segment an image based on regions with similar color. You can display the image in different color spaces to differentiate objects in the image.

Acquire Live Images in the Color Thresholder App

You can perform color thresholding on an image acquired from a live USB webcam.

Image Segmentation Using Point Clouds in the Color Thresholder App

Use point cloud control to segment an image by selecting a range of colors belonging to the object to isolate.