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METHOD AND SYSTEM FOR FUZZY CLUSTERING OF IMAGES

  • US 20090074305A1
  • Filed: 11/11/2008
  • Published: 03/19/2009
  • Est. Priority Date: 03/28/2001
  • Status: Active Grant
First Claim
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1. A method for clustering a set of N images into P final clusters, where N and P are integers, comprising:

  • (a) calculating at least one similarity measure Si,j between members of each pair of images, where said Si,j represents the similarity measure between an ith image and an jth image with i and j being image indices;

    (b) calculating a total connectivity value for each of the images remaining to be clustered, where said total connectivity value for each image being defined as a sum of a function f of the similarity measures associated with that image;

    (c) identifying, from among said images remaining to be clustered, a maximum total connectivity value Tmax corresponding to an image Imax, where said image Imax belonging to a current cluster C which initially includes all images remaining to be clustered;

    (d) removing, from the current cluster C, at least one image based on at least one of its similarity measure with image Imax and its total connectivity value within the current cluster C;

    (e) adding, to the current cluster C, images having a similarity measure that is greater than a threshold T3;

    (f) calculating, for each image within the current cluster C, a total connectivity value based on those images within the current cluster C;

    (g) removing, from the current cluster C, those images having a total connectivity value less than a threshold T4; and

    (h) repeating said steps (f) and (g) until no further images are removed to thereby establish the current cluster C as one of the final clusters.

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