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Image segmentation method

  • US 6,839,462 B1
  • Filed: 12/22/1997
  • Issued: 01/04/2005
  • Est. Priority Date: 12/23/1996
  • Status: Expired due to Fees
First Claim
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1. A method of classifying grey scale image data according to different region types within the image, the method comprising:

  • assigning a single feature value to each datum;

    reducing the resolution of each value of the data;

    generating a histogram of the reduced resolution value data; and

    , performing a fast fuzzy c-means clustering algorithm on all of the histogram data, so as to minimize a fuzzy object function Jm(W, v), wherein Jm(W, v) is defined by the equation Jm

    (W,v)
    =

    g=GminGmax








    i=1c






    f

    (g)


    (wig)nl

    (dig)2
    ,


    using generated values f(g) of said reduced resolution histogram, and wherein;

    c represents a number of clusters in the image;

    Gmin and Gmax represent respectively a minimum and maximum grey scale value q in the image;

    m is a fuzzy weighting exponent;

    w is a fuzzy partition of the histogram data with entries wig which correspond to a membership value of each grey scale value g in a cluster i of the image; and

    , dig is a Euclidian distance between a grey scale value q and v1.

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