ImageMagick: MagickCore, C API for ImageMagick: Segment an Image with Thresholding Fuzzy c-Means
Author: ImageMagick Studio LLC
Description: ImageMagick® is a software suite to create, edit, and compose bitmap images. It can read, convert and write images in a variety of formats (about 100) including GIF, JPEG, JPEG-2000, PNG, PDF, PhotoCD, TIFF, and DPX. Use ImageMagick to translate, flip, mirror, rotate, scale, shear and transform images, adjust image colors, apply various special effects, or draw text, lines, polygons, ellipses and Bézier curves. ImageMagick is free software delivered as a ready-to-run binary distribution or as source code that you can freely use, copy, modify, and distribute. Its license is compatible with the GPL. It runs on all major operating systems. The functionality of ImageMagick is typically utilized from the command line or you can use the features from programs written in your favorite programming language. Choose from these interfaces: MagickCore (C), MagickWand (C), ChMagick (Ch), Magick++ (C++), JMagick (Java), L-Magick (Lisp), PascalMagick (Pascal), PerlMagick (Perl), MagickWand for PHP (P [cell cut: 1167 characters, first 1000 kept]
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## SegmentImage

SegmentImage() segment an image by analyzing the histograms of the color components and identifying units that are homogeneous with the fuzzy C-means technique.

The format of the SegmentImage method is:

      MagickBooleanType SegmentImage(Image *image,
        const ColorspaceType colorspace,const MagickBooleanType verbose,
        const double cluster_threshold,const double smooth_threshold)

A description of each parameter follows.

##### image

the image.

##### colorspace

Indicate the colorspace.

##### verbose

Set to MagickTrue to print detailed information about the identified classes.

##### cluster_threshold

This represents the minimum number of pixels contained in a hexahedra before it can be considered valid (expressed as a percentage).

##### smooth_threshold

the smoothing threshold eliminates noise in the second derivative of the histogram. As the value is increased, you can expect a smoother second derivative.

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