Catalog of Functionality > Image Processing Toolkit > Classification and Segmentation
  

Classification and Segmentation
IPCLASSIFY
Performs supervised classification using the maximum likelihood classifier
IPCLUSTER
Performs image segmentation using K-means clustering based on regional statistical measures of the mean, mode, minimum, maximum and/or range of the image pixels
REGION_COUNT
Computes the number of regions in an image
REGION_FIND
Locates a possible seed point for a region in an image
REGION_GROW
Grows homogeneous regions in an image, where homogeneity is based on the region average
REGION_MERGE
Merges homogeneous regions in an image, where homogeneity is based on the region average
REGION_SPLIT
Splits homogeneous regions in an image, where the homogeneity is based on the region range
REGION_STATS
Performs several statistical calculations on specified regions in an image
THRESH_ADAP
Performs adaptive thresholding on an image
THRESHOLD
Performs either binary or grayscale global thresholding on an image

Version 2017.0
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