
vmindis(1)                   Khoros                    vmindis(1)

PROGRAM
     vmindis - Minimum Distance Classifier

SYNTAX
     vmindis

     -i1            input image

     -i2            input image

     -o             output image specifying which vector belongs
                    to what cluster

     [-b]            specifies the border width in pixels
                    (default = 0)

     [-V]           Gives the version for vmindis

     [-U]           Gives the usage for vmindis

     [-P]           Prompts for command line options

     [-A [file1]]   Creates the answer file called vmindis.ans or
                    file1

     [-a [file1]]   Uses vmindis.ans or file1 as the answer file

DESCRIPTION
     vmindis is a simple minimum distance classifier. The dis-
     tance metric used to the Euclidean distance. This routine
     accepts two images as the input. The image that corresponds
     to the -i1 argument is the image that needs to be classi-
     fied. This image can be have as many data bands as neces-
     sary. The number of data bands depicts the dimensionality of
     the vectors. Each pixel in the image is a vector with dimen-
     sionality of the number of data bands.

     The other input image which corresponds to the -i2 argument
     is the prototype image. The last data band of this image is
     the class data band. This image must contain the same number
     of data bands as the other input image plus an extra data
     band that represents the class mapping. This image would
     most likely have been created by vkmeans or some other rou-
     tine that will give cluster centers. This image contains
     vectors that correspond to the prototype of each class.

     As stated above the center image's last data band is a class
     data band. The class data band simply maps each vector in
     the center image to the final class.

     At this point most class images must be created manually.  A
     class image can be created by using pseudo color in
     xvdisplay on the resulting clustered image from the vkmeans
     routine. Vcustom can then be used to create the class image.
     Finally vbandcomb can be used to add the class image data to
     the center image. Normally one would over cluster using
     vkmeans then reduce the space down. So vkmeans might produce
     100 clusters but, really only 3 clusters are desired. Pseudo
     color in xvdisplay and vcustom can be used to reduce the
     space down and create a class image. The class data might
     map cluster center vectors 1-50 to class 1, vectors 51-60 to
     class 2 and vectors 61-100 to class 3. When the vmindis rou-
     tine is run, the result would be a classified image of three
     classes.

     The border option (-b) allows the user to specify a border
     width, in pixels, encompassing the image. The border region
     is skipped by vmindis when classification is performed. This
     useful if neighborhood operators have been used previously
     and have not updated edge pixels.

     All input images must be of data storage type FLOAT.

REQUIRED ARGUMENTS
     -i1    type: infile
            desc: input image

     -i2    type: infile
            desc: input image

     -o     type: outfile
            desc: output image specifying which vector belongs to
            what cluster

OPTIONAL ARGUMENTS
     -b     type: integer
            desc:  specifies the border width in pixels (default
            = 0)
            default: 0
            bounds: 0 < [-b] < 100

EXAMPLES
     vmindis -i1 ariel_image.xv -i2 vkmeans_centers -b 5 -o test

     ariel_image.xv is a 5 band image; thus, each vector has
     dimensionality of 5, vkmeans_centers image is a 6 band
     image, 5 bands are the cluster center values produced by
     vkmeans and 1 class band.  The border that vmindis will
     ignore is 5 pixels wide. the output image will be a single
     band image called test.

SEE ALSO
     intro(1), verror(3), vgparms(3), vutils(3), lvmindis(3)

RESTRICTIONS
     All input images must be of data storage type FLOAT.

COPYRIGHT
     Copyright 1991, University of New Mexico.  All rights
     reserved.

Khoros                    Release: 1.0                          1

