Image analysis – Pattern recognition – Classification
Reexamination Certificate
2007-08-14
2008-12-02
Carter, Aaron W (Department: 2624)
Image analysis
Pattern recognition
Classification
C382S155000, C706S001000, C707S793000
Reexamination Certificate
active
07460717
ABSTRACT:
An approach to clustering a set of images based on similarity measures employs a fuzzy clustering paradigm in which each image is represented by a node in a graph. The graph is ultimately partitioned into subgraphs, each of which represent true clusters among which the various images are distributed. The partitioning is performed in a series of stages by identifying one true cluster at each stage, and removing the nodes belonging to each identified true cluster from further consideration so that the remaining, unclustered nodes may then be grouped. At the beginning of each such stage, the nodes that remain to be clustered are treated as all belonging to a single candidate cluster. Nodes are removed from this single candidate cluster in accordance with similarity and connectivity criteria, to arrive at a true cluster. The member nodes of this true cluster are then removed from further consideration, prior to the next stage in the process.
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Jafarkhani Hamid
Tarokh Vahid
AT&T Corp.
Carter Aaron W
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