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Automatic Image Quality Assessment with Application in Biometrics

H. Fronthaler, K. Kollreider and J. Bigun
Halmstad University
SE-30118, Sweden
{hartwig.fronthaler, klaus.kollreider, josef.bigun}[at]ide.hh.se

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Abstract
A method using local features to assess the quality of
an image, with demonstration in biometrics, is proposed.
Recently, image quality awareness has been found to increase
recognition rates and to support decisions in multimodal
authentication systems significantly. Nevertheless,
automatic quality assessment is still an open issue, especially
with regard to general tasks. Indicators of perceptual
quality like noise, lack of structure, blur, etc. can be retrieved
from the orientation tensor of an image, but there
are few studies reporting on this. Here we study the orientation
tensor with a set of symmetry descriptors, which can
be varied according to the application. Allowed classes of
local shapes are generically provided by the user but no
training or explicit reference information is required. Experimental
results are given for fingerprint. Furthermore,
we indicate the applicability of the proposed method to face
images.