Automatic Image Quality Assessment with Application in Biometrics

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...

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Bibliographic Details
Main Authors: Fronthaler, H., Kollreider, K., Bigun, J.
Format: Conference Proceeding
Language:English
Subjects:
Authentication
Biometrics
Fingerprint recognition
Image analysis
Image processing
Image quality
Image recognition
Image retrieval
Multi-stage noise shaping
Quality assessment
Shape
TECHNOLOGY
TEKNIKVETENSKAP
Tensile stress
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Description
Summary: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.
ISSN:2160-7508
2160-7516
DOI:10.1109/CVPRW.2006.36