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170structuring element file.Segment and autosegment are implementations of automatic unsupervised imagesegmentation. They use a method based on histogram equalization to generatean initial segmentation. Then, EM is used to fit a Gaussian mixture with K components.For the Segment algorithm, K is specified by the user; for Autosegment,the user specifies a maximum value of K and the program chooses the best Kbased on a modified version of BIC (note that this does not use pseudolikelihood).All of these methods are designed for greyscale images; if the image is color,then the red color band is used as the image. These methods are quite fast;autosegment can examine values of K from 2 to 12 for a typical 256x256 imagein under a minute. There are some restrictions on image size due to memoryconstraints. These limits are hard-coded into the modified XV version, but theycan be altered by editing the source code and recompiling.A.2 C codegreyhist.c - This program finds the marginal histogram of an image. Input files:greyhistaux.txt (width, height), greyhistin.asc (ascii greyscale integers only). Outputfile: greyhistout.txt.covascii.c - This program computes the covariance matrix of the image and 4lags (the 4 adjacent neighbors preceding each pixel in raster scan order). Inputfiles: covinput.txt (width, height), covimagein.txt (ascii greyscale integers only).Output file: covoutput.txt.emheqpoisson.c - This program uses EM to fit a Poisson mixture model for segmentation,using histogram equalization as the initial segmentation. Final classificationis done without mixture probabilities. Input files: eminput.txt (width,height, # of segments) emimagein.asc (ascii greyscale integers only). Output files: