Abstract book (pdf) - ICPR 2010

is integrate the features at a descriptor level, in this case arises the problem of normalizing both cues. A significant progress
in the last years in object recognition has provided the bag-of-words framework that again deals with the problem of
feature combination through the definition of vocabularies of visual words. Inspired in this framework, here we present
perceptual textons that will allow to fuse color and texture at the level of p-blobs, which is our feature detection step.
Feature representation is based on two uniform spaces representing the attributes of the p-blobs. The low-dimensionality
of these text on spaces will allow to bypass the usual problems of previous approaches. Firstly, no need for normalization
between cues; and secondly, vocabularies are directly obtained from the perceptual properties of text on spaces without
any learning step. Our proposal improve current state-of-art of color-texture descriptors in an image retrieval experiment
over a highly diverse texture dataset from Corel.
10:20-10:40, Paper TuAT6.5
Illumination Estimation of 3D Surface Texture based on Active Basis
Dong, Junyu, Ocean Univ. of China
Su, Liyuan, Ocean Univ. of China
Duan, Yuanxu, Alcatel-Lucent R&D
This paper describes an approach to estimate illumination directions of 3D surface texture based on Active Basis. Instead
of applying Gabor wavelet transform to extract texture features, we represent our texture features with a simple Haar
feature to improve efficiency. The Active Basis model can be learned from training image patches by the shared pursuit
algorithm. The base histogram can then be obtained based on each model. We measure the illumination directions by minimizing
the Euclidean distance and the entropy difference of base histograms between the test image and the training sets.
Experimental results demonstrate the effectiveness and accuracy of the proposed approach.
TuAT7 Dolmabahçe Hall C
Security and Privacy Regular Session
Session chair: Veldhuis, Raymond (Univ of Twente)
09:00-09:20, Paper TuAT7.1
Binary Discriminant Analysis for Face Template Protection
Feng, Y C, Hong Kong Baptist Univ.
Yuen, Pong C, Hong Kong Baptist Univ.
Biometric cryptosystem (BC) is a very secure approach for template protection because the stored template is encrypted.
The key issues in BC approach include(I) limited capability in handling intra-class variations and (ii) binary input is required.
To overcome these problems, this paper adopts the concept of discriminative analysis and develops a new binary
discriminant analysis (BDA) method to convert a real valued template to a binary template. Experimental results on CMU-
PIE and FRGC face databases show that the proposed BDA method outperforms existing template binarization schemes.
09:20-09:40, Paper TuAT7.2
Renewable Minutiae Templates with Tunable Size and Security
Yang, Bian, Gjovik Univ. Coll.
Busch, Christoph, Gjovik Univ. Coll.
Gafurov, Davrondzhon, Gjovik Univ. Coll.
Bours, Patrick, Gjovik Univ. Coll.
A renewable fingerprint minutiae template generation scheme is proposed to utilize random projection for template diversification
in a security enhanced way. The scheme first achieves absolute pre-alignment over local minutiae quadruplets
in the original template and results in a fix-length feature vector; and then encrypts the feature vector by projecting it to
multiple random matrices and quantizing the projected result; and finally post-process the resultant binary vector in a size
and security tunable way to obtain the final protected minutia vicinity. Experiments on the fingerprint database
FVC2002DB2_A demonstrate the desirable biometric performance of the proposed scheme.
- 79 -