P196 - BIOSIG 2012 - Proceedings of the 11th International Conference of the Biometrics Special Interest Group
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- KonferenzbeitragApplying fusion in thermal face recognition(BIOSIG 2012, 2012) Váňa, Jan; Mráček, Stepán; Poursaberi, Ahmad; Yanushkevich, Svetlana; Drahanský, MartinFace recognition based on thermal images has minor importance in comparison to visible light spectrum recognition. Nevertheless, in applications such as livelyness detection or fever scan, thermal face recognition is used as a stand-alone module, or as part of a multi-modal biometric system. This paper investigates combinations of many methods, used for thermal face recognition, and introduces some new and modified algorithms, which have not been used in the area as of yet. Moreover, we show that the best method is always limited to a certain database (input data). In order to address this problem, the multi-algorithmic biometric fusion, based on the logistic regression, is deployed.
- KonferenzbeitragFace verification using Gabor filtering and adapted Gaussian mixture models(BIOSIG 2012, 2012) Shafey, Laurent El; Wallace, Roy; Marcel, SébastienThe search for robust features for face recognition in uncontrolled environments is an important topic of research. In particular, there is a high interest in Gaborbased features which have invariance properties to simple geometrical transformations. In this paper, we first reinterpret Gabor filtering as a frequency decomposition into bands, and analyze the influence of each band separately for face recognition. Then, a new face verification scheme is proposed, combining the strengths of Gabor filtering with Gaussian Mixture Model (GMM) modelling. Finally, this new system is evaluated on the BANCA and MOBIO databases with respect to well known face recognition algorithms. The proposed system demonstrates up to 52\% relative improvement in verification error rate compared to a standard GMM approach, and outperforms the state-of-the-art Local Gabor Binary Pattern Histogram Sequence (LGBPHS) technique for several face verification protocols on two different databases.
- KonferenzbeitragNear infrared face recognition using orientation-based face patterns(BIOSIG 2012, 2012) Zheng, YufengAn orientation-based face recognition method is proposed and applied to near infrared images in this paper. Two algorithms, FPW (face pattern word) and FPB (face pattern byte), are derived from the orientation-based method. The FPW (or FPB) algorithm actually extracts the orientational information using a set of Gabor wavelet transforms, and uses Hamming distance (HD) for face identification. The bit code of orientations are optimized with respect to HD and put into a 32-bit word (FPW) or 8-bit byte (FPB). The performance is evaluated by face recognition rate and compared with three classical algorithms, PCA, LDA and EBGM (elastic bunch graph matching). Our experiments are conducted with a ASUNIR face database that currently consists of near infrared (NIR) images from 79 subjects. The experimental results show that the FPW algorithm achieves 98.43% of recognition rate; while the results of PCA, LDA and EBGM are 74.68%, 94.94% and 96.20%, respectively.
- KonferenzbeitragAddressing biometrics security and privacy related challenges in China(BIOSIG 2012, 2012) Mok, Sum Yu; Kumar, AjayThere has been significant advancement improvement in the capabilities of biometrics and data protection technologies in last decade. The significant reduction in cost, improvements in speed and accuracy has resulted in increased deployment of such technologies in day-to-day business and public utilities. The increasing use of biometrics and data protection technologies has also raised concern on the unethical use of personal information. There are increasing number of incidents and concerns in the public over the infringement of personal privacy in China. This paper has investigated such emerging privacy related concerns in the deployment of biometrics and data protection technologies in China. This paper also includes a study on public attitudes toward such technologies and attempts to make comparison with the same in the difference with such emerging concerns in other developed countries. This paper has developed an online survey to ascertain people's understanding on the various aspects of privacy and thus willingness to tradeoff with the benefits of increased security. The online survey was conducted in February – March 2012 and revealed great deal of information from the 305 Hong Kong people. We have attempted to analyze the survey results which illustrate interesting findings on the use of CCTV, biometrics technologies, social networking, disclosure of personal information and recent (2012) privacy policy adjustments in popular websites.
- KonferenzbeitragOn the effectiveness of local binary patterns in face anti-spoofing(BIOSIG 2012, 2012) Chingovska, Ivana; Anjos, André; Marcel, SébastienSpoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with ~15% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types.
- KonferenzbeitragCurvelet transform-based features extraction for fingerprint identification(BIOSIG 2012, 2012) Guesmi, Hanene; Trichili, Hanene; Alimi, Adel M.; Solaiman, BaselThe performance of the fingerprint identification process highly depends on its extractor of fingerprint features. So, to reduce the dimensionality of the fingerprint image and improve the identification rate, a fingerprint features extraction method based on Curvelet transform is proposed and presented in this paper. Thus, our paper focuses on presenting of our Curvelet-based fingerprint features extraction method. This method consists of two steps: decompose the fingerprint into set of sub-bands by the Curvelet transform and automatic extraction of the most discriminative statistical features of these sub-bands. An extensive experimental evaluation shows that the proposed method is effective and encouraging.
- KonferenzbeitragSIFT based fingerprint corepoint localization(BIOSIG 2012, 2012) Goyal, Kunal; Malekar, Rutvik; Jindal, AkhilThe detection of singular points (core and delta), accurately and reliably , is very important for classification and matching of fingerprints.This paper presents a new approach for core point detection based on Scale Invariant Feature Transform (SIFT) operation. Firstly, SIFT points are extracted, then reliability and ridge frequency criteria are applied to reduce the candidate point required to make a decision on the core point. Finally a suitable mask is applied to detect an accurate core point. Experiments on FVC2002 and FVC2004 database show that our approach locates a unique reference point with high accuracy.Results have been compared with existing methods in terms of accuracy of core point detection. To make the algorithm reliable, a simple point based matching has been implemented.
- KonferenzbeitragExploiting data-rich regions of interest in static signature verification(BIOSIG 2012, 2012) Johnson, Emma P. S.; Guest, Richard M.The identification and subsequent utilisation of regions of interest within biometric sample images can provide useful information that can benefit recognition performance. If a specific area of a biometric sample is data-rich in terms of feature quantity or quality then these regions of specific interest can be exploited, for example in terms of processing algorithm selection and information weighting. Also, if intra-area stability/feature repeatability can be obtained a-priori this information may be used to enhance biometric systems. The objective of the work documented in this paper is to develop a best practice framework for the utilisation of sub regions of interest within biometric signature images to enable an optimisation of systems. Our hypothesis is that by sub-dividing a signature image, information richness within sub-divisions can be exploited by weighting grid zones. Signature images were divided using 14 experimental template patterns. Using the GPDS-960 off-line signature corpus, the verification performance achieved using each weighted method was compared against a non-gridded baseline implementation. Significant improvements were noted for a number of the defined grid zones indicating the potential for the approach.
- KonferenzbeitragLocal binary patterns and neural network based technique for robust face detection and localization(BIOSIG 2012, 2012) Nikisins, Olegs; Greitans, ModrisThis paper proposes an adaptation of Local Binary Pattern (LBP) operator for the design of the precise face localization technique. Presented approach is divided into three main stages: face detection, detection of eye regions and localization of eye pupils. Introduced optimization principles and the discriminative power of the LBP significantly reduces the number of features used to describe the classes and simplifies the structure of the utilized classifier, namely, artificial neural network. The combination of the reduced dimensionality of the feature space and the presented histogram-based sliding window makes the proposed algorithm well applicable for the task of precise face localization in high resolution images. The parameters of the algorithms are evaluated on a color FERET database.
- KonferenzbeitragEvaluation of independence between palm vein and fingerprint for multimodal biometrics(BIOSIG 2012, 2012) Yamada, Shigefumi; Endoh, Toshio; Shinzaki, TakashiMultimodal biometrics provides high recognition accuracy and population coverage by combining different biometric sources. However, some multimodal biometrics may obtain smaller-than-expected improvement of recognition accuracy if the combined biometric sources are dependent in terms of a false acceptance by mistakenly perceiving biometric features from two different persons as being from the same person. In this paper, we propose our multimodal biometric prototype that captures a palm vein and three fingerprints simultaneously and we evaluate whether or not their combination is statistically independent. By evaluating false acceptance using the palm vein images and the fingerprint images collected with our prototype, we confirmed that the combination of the palm vein and the fingerprints is almost independent.