Abstract book (pdf) - ICPR 2010

TuAT9 Upper Foyer
Biometrics Poster Session
Session chair: Dobrišek, Simon (University of Ljubljana)
09:00-11:10, Paper TuAT9.1
Image Specific Error Rate: A Biometric Performance Metric
Tabassi, Elham, NIST
Image-specific false match and false non-match error rates are defined by inheriting concepts from the biometric zoo. These
metrics support failure mode analyses by allowing association of a covariate (e.g., dilation for iris recognition) with a matching
error rate without having to consider the covariate of a comparison image. Image-specific error rates are also useful in detection
of ground truth errors in test datasets. Images with higher image-specific error rates are more ``difficult’’ to recognize,
so these metrics can be used to assess the level of difficulty of test corpora or partition a corpus into sets with varying level
of difficulty. Results on use of image-specific error rates for ground-truth error detection, covariate analysis and corpus partitioning
is presented.
09:00-11:10, Paper TuAT9.2
Low Cost and Usable Multimodal Biometric System based on Keystroke Dynamics and 2D Face Recognition
Giot, Romain, Univ. de Caen, Basse-Normandie – CNRS
Hemery, Baptiste, Univ. de CAEN
Rosenberger, Christophe, Lab. GREYC
We propose in this paper a low cost multimodal biometric system combining keystroke dynamics and 2D face recognition.
The objective of the proposed system is to be used while keeping in mind: good performances, acceptability, and espect of
privacy. Different fusion methods have been used (min, max, mul, svm, weighted sum configured with genetic algorithms,
and, genetic programming) on the scores of three keystroke dynamics algorithms and two 2D face recognition ones. This
multimodal biometric system improves the recognition rate in comparison with each individual method. On a chimeric database
composed of 100 individuals, the best keystroke dynamics method obtains an EER of 8.77%, the best face recognition
one has an EER of 6.38%, while the best proposed fusion system provides an EER of 2.22%.
09:00-11:10, Paper TuAT9.3
Parallel versus Hierarchical Fusion of Extended Fingerprint Features
Zhao, Qijun, The Hong Kong Pol. Univ.
Liu, Feng, The Hong Kong Pol. Univ.
Zhang, Lei, The Hong Kong Pol. Univ.
Zhang, David, The Hong Kong Pol. Univ.
Extended fingerprint features such as pores, dots and incipient ridges have been increasingly attracting attention from researchers
and engineers working on automatic fingerprint recognition systems. A variety of methods have been proposed to
combine these features with the traditional minutiae features. This paper comparatively analyses the parallel and hierarchical
fusion approaches on a high resolution fingerprint image dataset. Based on the results, a novel and more effective hierarchical
approach is presented for combining minutiae, pores, dots and incipient ridges.
09:00-11:10, Paper TuAT9.4
Feature Band Selection for Multispectral Palmprint Recognition
Guo, Zhenhua, The Hong Kong Pol. Univ.
Zhang, Lei, The Hong Kong Pol. Univ.
Zhang, David, The Hong Kong Pol. Univ.
Palm print is a unique and reliable biometric characteristic with high usability. Many palm print recognition algorithms and
systems have been successfully developed in the past decades. Most of the previous works use the white light sources for illumination.
Recently, it has been attracting much research attention on developing new biometric systems with both high
accuracy and high anti-spoof capability. Multispectral palm print imaging and recognition can be a potential solution to such
systems because it can acquire more discriminative information for personal identity recognition. One crucial step in developing
such systems is how to determine the minimal number of spectral bands and select the most representative bands to
build the multispectral imaging system. This paper presents preliminary studies on feature band selection by analyzing hyper
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