Abstract book (pdf) - ICPR 2010

evaluation of micropattern representations on four forms of Gabor features for face recognition. Three evaluation rules
are proposed and observed for a fair comparison. To reduce the high feature dimensionality problem, uniform quantization
is used to partition the spatial histograms. The experimental results reveal that: 1) micropattern representation based on
Gabor magnitude features outperforms the other three representations, and the performances of the other three are comparable;
and 2) micropattern representation based on the combination of Gabor magnitude and phase features performs
the best.
09:00-11:10, Paper TuAT9.39
Block Pyramid based Adaptive Quantization Watermarking for Multimodal Biometric Authentication
Ma, Bin, Beihang Univ.
Li, Chunlei, Beihang Univ.
Wang, Yunhong, Beihang Univ.
Zhang, Zhaoxiang, Beihang Univ.
Wang, Yiding, North China Univ. of Tech.
This paper proposes a novel robust watermarking scheme to embed fingerprint minutiae into face images for multimodal
biometric authentication. First, a block pyramid is layered according to the block-wise face region distinctiveness estimated
by Adaboost; upper level indicates informative spacial regions. Then, we adopt a first-order statics QIM method to perform
watermark embedding in each pyramid level. Numeric watermark bits with higher priority are embedded into upper pyramid
level with a larger embedding strength. By joint differentiation of host image regions and watermark bits priority, our
scheme achieves a trade-offs among watermarking robustness, capacity and fidelity. Experimental results demonstrate
that our approach guarantees the robustness of hidden biometric data, while preserving the distinctiveness of host biometric
images.
09:00-11:10, Paper TuAT9.40
A Topologic Approach to User-Dependent Key Extraction from Fingerprints
Gudkov, Vladimir, Sonda
Ushmaev, Oleg, Russian Acad. of Sciences
The paper briefly describes an approach to key extraction from fingerprint images based on topological descriptors of
minutiae point neighborhood. The approach allows designing biometric encryption procedures with variable key length
and successful decryption rate.
09:00-11:10, Paper TuAT9.41
Robust Face Recognition using Block-Based Bag of Words
Li, Zisheng, The Univ. of Electro-Communications
Imai, Jun-Ichi, The Univ. of Electro-Communications
Kaneko, Masahide, The Univ. of Electro-Communications
A novel block-based bag of words (BboW) method is proposed for robust face recognition. In our approach, a face image
is partitioned into multiple blocks, dense SIFT features are then calculated and vector quantized into different codewords
on each block respectively. Finally, histograms of codeword distribution on each local block are concatenated to represent
the face image. Experimental results on AR database show that only using one neutral expression frame per person for
training, our method can obtain excellent face recognition results on face images with extreme expressions, variant illumination,
and partial occlusions. Our method also achieves an average recognition rate of 100% on XM2VTS database.
09:00-11:10, Paper TuAT9.42
Analysis of Fingerprint Pores for Vitality Detection
Marcialis, Gian Luca, Univ. of Cagliari
Roli, Fabio, Univ. of Cagliari
Tidu, Alessandra, Univ. of Cagliari
Spoofing is an open-issue for fingerprint recognition systems. It consists in submitting an artificial fingerprint replica from
a genuine user. Current sensors provide an image which is then processed as a true fingerprint. Recently, the so-called 3 rd -
level features, namely, pores, which are visible in high-definition fingerprint images, have been used for matching. In this
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