Image analysis – Pattern recognition – Template matching
Reexamination Certificate
2005-08-26
2009-11-17
Hung, Yubin (Department: 2624)
Image analysis
Pattern recognition
Template matching
C382S100000, C382S181000, C382S209000, C382S305000, C382S274000
Reexamination Certificate
active
07620249
ABSTRACT:
A first pattern (A) is represented by a first ordered set of elements (xi) each having a value whilst a second pattern (B) is represented by a second ordered set of element (ui) each having a value. The patterns are analysed by iteratively performing the steps of: selecting (e.g. at random) a plurality m of elements from the first ordered set; for each selected element xiof the first ordered set, selecting an element uifrom the second ordered set, such that the selected elements of the second ordered set have, within the second ordered set, a set of positional relationships relative to each other that is the same as, or a transformation of, the set of positional relationships that the selected plurality of elements of the first ordered set have relative to each other, comparing the value of each of the selected elements of the first ordered set with the value of the correspondingly positioned selected element of the second ordered set in accordance with a predetermined match criterion to produce a decision that the selected plurality of elements of the first ordered set does or does not match the selected plurality of elements of the second ordered set; and in the event of a match, updating at least one similarity score (SAB). In the selection of the elements of the second ordered set, one chooses (e.g. at random) at least one parameter (R, β, α) and selects elements having a set of positional relationships (di′, di″)) that is transformed from the positional relationship set diof the selected elements of the first ordered set in accordance with the parameter(s). This transformation may include one or more of rotation, reflection or scaling. Other aspects include biasing the selection of the elements of the first ordered set towards a large extent, and of introducing variations in the number of elements selected, with the similarity score being updated by an amount that is a function of the number of elements. The method may also be applied to a single image.
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Bayat Ali
British Telecommunications public limited company
Hung Yubin
Nixon & Vanderhye PC
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