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.
|Global image threshold using Otsu's method|
|Multilevel image thresholds using Otsu’s method|
|Global histogram threshold using Otsu's method|
|Adaptive image threshold using local first-order statistics|
|Select contiguous image region with similar gray values using flood-fill technique|
|Segment image into foreground and background using active contours (snakes) region growing technique|
|Segment image into foreground and background using graph-based segmentation|
|Segment image into foreground and background using iterative graph-based segmentation|
|Segment image into two or three regions using geodesic distance-based color segmentation|
|Binary image segmentation using fast marching method|
|Calculate weights for image pixels based on image gradient|
|Calculate weights for image pixels based on grayscale intensity difference|
|K-means clustering based image segmentation|
|K-means clustering based volume segmentation|
|2-D superpixel oversegmentation of images|
|3-D superpixel oversegmentation of 3-D image|
This topic provides an overview of the Image Segmenter app and its capabilities.
Image Processing Toolbox Image Data package contains sample 3-D volumetric data.
This example shows how to segment an image and create a binary mask image using the Color Thresholder app.
You can perform color thresholding on an image acquired from a live USB webcam.
This example shows how to segment an image using the point cloud control in the Color Thresholder app.
This example shows how to perform land type classification based on color features using K-means clustering and superpixels.
This example shows how to perform a 3-D segmentation using active contours (snakes).
This example shows how to segment a volume in the Volume Segmenter app.
This example shows how to create a semantic segmentation of a volume using the Volume Segmenter app.