IAPR International Conference on Biometrics (ICB)
2018 International Conference on Biometrics (ICB)
20-23 Feb. 2018
Showing 1-25 of 55
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Biometrics (ICB), 2018 International Conference on
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Provides an abstract for each of the keynote presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.Show More
Fingerprint Distortion Rectification Using Deep Convolutional Neural Networks
Ali Dabouei;Hadi Kazemi;Seyed Mehdi Iranmanesh;Jeremy Dawson;Nasser M. Nasrabadi
Publication Year: 2018,Page(s):1 - 8
Cited by: Papers (24)
Elastic distortion of fingerprints has a negative effect on the performance of fingerprint recognition systems. This negative effect brings inconvenience to users in authentication applications. However, in the negative recognition scenario where users may intentionally distort their fingerprints, this can be a serious problem since distortion will prevent recognition system from identifying malic...Show More
Robust Minutiae Extractor: Integrating Deep Networks and Fingerprint Domain Knowledge
Publication Year: 2018,Page(s):9 - 16
We propose a fully automatic minutiae extractor, called MinutiaeNet, based on deep neural networks with compact feature representation for fast comparison of minutiae sets. Specifically, first a network, called CoarseNet, estimates the minutiae score map and minutiae orientation based on convolutional neural network and fingerprint domain knowledge (enhanced image, orientation field, and segmentat...Show More
Comparative Study of Digital Fingerprint Quality Assessment Metrics
Zhigang Yao;Jean-Marie Le Bars;Christophe Charrier;Christophe Rosenberger
Publication Year: 2018,Page(s):17 - 22
Cited by: Papers (3)
The quality assessment of biometric data proceeds as a toll to decide whether a biometric sample may be used to generate the user's reference template. Many studies showed its significant impact on the subsequent performance of the biometric system. Since many metrics are proposed for this purpose by researchers or standardization institutions, their relevance should be studied in particular to ev...Show More
Filter Design Based on Spectral Dictionary for Latent Fingerprint Pre-enhancement
Publication Year: 2018,Page(s):23 - 30
Cited by: Papers (10)
We introduce a pre-enhancement algorithm to improve efficiency of the automatic fingerprint identification systems (AFIS) for latent fingerprint search. The proposed algorithm employs learning to construct a spectral dictionary from spectral responses of a Gabor filter bank in the frequency domain. Given an input latent fingerprint, the spectral dictionary yields a set of appropriate filters for e...Show More
Fingerprint Synthesis: Evaluating Fingerprint Search at Scale
Publication Year: 2018,Page(s):31 - 38
Cited by: Papers (30)
A database of a large number of fingerprint images is highly desired for designing and evaluating large scale fingerprint search algorithms. Compared to collecting a large number of real fingerprints, which is very costly in terms of time, effort and expense, and also involves stringent privacy issues, synthetic fingerprints can be generated at low cost and does not have any privacy issues to deal...Show More
Evolutionary Methods for Generating Synthetic MasterPrint Templates: Dictionary Attack in Fingerprint Recognition
Publication Year: 2018,Page(s):39 - 46
Cited by: Papers (17)
Recent research has demonstrated the possibility of generating "Masterprints" that can be used by an adversary to launch a dictionary attack against a fingerprint recognition system. Masterprints are fingerprint images that fortuitously match with a large number of other fingerprints thereby compromising the security of a fingerprint-based biometric system, especially those equipped with small-siz...Show More
Hierarchical Multi-class Iris Classification for Liveness Detection
Publication Year: 2018,Page(s):47 - 53
Cited by: Papers (7)
In modern society, iris recognition has become increasingly popular. The security risk of iris recognition is increasing rapidly because of the attack by various patterns of fake iris. A German hacker organization called Chaos Computer Club cracked the iris recognition system of Samsung Galaxy S8 recently. In view of these risks, iris liveness detection has shown its significant importance to iris...Show More
Securing Minutia Cylinder Codes for Fingerprints through Physically Unclonable Functions: An Exploratory Study
Rosario Arjona;Miguel Angel Prada-Delgado;Iluminada Baturone;Arun Ross
Publication Year: 2018,Page(s):54 - 60
Cited by: Papers (11)
A number of personal devices, such as smartphones, have incorporated fingerprint recognition solutions for user authentication purposes. This work proposes a dual-factor fingerprint matching scheme based on P-MCCs (Protected Minutia Cylinder-Codes) generated from fingerprint images and PUFs (Physically Unclonable Functions) generated from device SRAMs (Static Random Access Memories). Combining the...Show More
Protecting Your Faces: MeshFaces Generation and Removal via High-Order Relation-Preserving CycleGAN
Publication Year: 2018,Page(s):61 - 68
Cited by: Papers (7)
Protecting person's face photos from being misused has been an important issue as the rapid development of ubiquitous face sensors. MeshFaces provide a simple and inexpensive way to protect facial photos and have been widely used in China. This paper treats MeshFace generation and removal as a dual learning problem and proposes a high-order relation-preserving CycleGAN framework to solve this prob...Show More
De-Mark GAN: Removing Dense Watermark with Generative Adversarial Network
Jinlin Wu;Hailin Shi;Shu Zhang;Zhen Lei;Yang Yang;Stan Z. Li
Publication Year: 2018,Page(s):69 - 74
Cited by: Papers (9)
This paper mainly considers the MeshFace verification problem with dense watermarks. A dense watermark often covers the crucial parts of face photo, thus degenerating the performance in the existing face verification system. The key to solving it is to preserve the ID information while removing the dense watermark. In this paper, we propose an improved GAN model, named De-mark GAN, for MeshFace ve...Show More
On Effectiveness of Anomaly Detection Approaches against Unseen Presentation Attacks in Face Anti-spoofing
Publication Year: 2018,Page(s):75 - 81
While face recognition systems got a significant boost in terms of recognition performance in recent years, they are known to be vulnerable to presentation attacks. Up to date, most of the research in the field of face anti-spoofing or presentation attack detection was considered as a two-class classification task: features of bona-fide samples versus features coming from spoofing attempts. The ma...Show More
Semi-adversarial Networks: Convolutional Autoencoders for Imparting Privacy to Face Images
Vahid Mirjalili;Sebastian Raschka;Anoop Namboodiri;Arun Ross
Publication Year: 2018,Page(s):82 - 89
In this paper, we design and evaluate a convolutional autoencoder that perturbs an input face image to impart privacy to a subject. Specifically, the proposed autoencoder transforms an input face image such that the transformed image can be successfully used for face recognition but not for gender classification. In order to train this autoencoder, we propose a novel training scheme, referred to a...Show More
Two-Stream Part-Based Deep Representation for Human Attribute Recognition
Publication Year: 2018,Page(s):90 - 97
Cited by: Papers (1)
Recognizing human attributes in unconstrained environments is a challenging computer vision problem. State-of-the-art approaches to human attribute recognition are based on convolutional neural networks (CNNs). The de facto practice when training these CNNs on a large labeled image dataset is to take RGB pixel values of an image as input to the network. In this work, we propose a two-stream part-b...Show More
Fine-Grained Multi-Attribute Adversarial Learning for Face Generation of Age, Gender and Ethnicity
Publication Year: 2018,Page(s):98 - 103
Cited by: Papers (11)
Since the Generative Adversarial Network (GAN) was proposed, facial image generation used for face recognition has been studied in recent two years. However, there are few GAN-based methods applied for fine-grained facial attribute analysis, such as face generation with precise age. In this paper, fine-grained multi-attribute GAN (FM-GAN) is presented, which can generate fine-grained face image un...Show More
Proceedings
The proceedings of this conference will be available for purchase through Curran Associates.
Biometrics (ICB), 2018 International Conference on
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