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This paper analyses the set of iris codes stored or used in an irisrecognition system as an f-granular space. The f-granulation is given byidentifying in the iris code space the extensions of the fuzzy concepts wolves,goats, lambs and sheep (previously introduced by Doddington as 'animals' of thebiometric menagerie) - which together form a partitioning of the iris codespace. The main question here is how objective (stable / stationary) thispartitioning is when the iris segments are subject to noisy acquisition. Inorder to prove that the f-granulation of iris code space with respect to thefuzzy concepts that define the biometric menagerie is unstable in noisyconditions (is sensitive to noise), three types of noise (localvar, motionblur, salt and pepper) have been alternatively added to the iris segmentsextracted from University of Bath Iris Image Database. The results of 180exhaustive (all-to-all) iris recognition tests are presented and commentedhere.

Noise Influence on the Fuzzy-Linguistic Partitioning of Iris Code Space