Open AccessProceedings Article
On the effectiveness of local binary patterns in face anti-spoofing
Ivana Chingovska,André Anjos,Sébastien Marcel +2 more
- pp 1-7
TLDR
This paper inspects 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 and concludes that LBP show moderate discriminability when confronted with a wide set of attack types.Abstract:
Spoofing 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.read more
Citations
More filters
Journal ArticleDOI
Face Spoof Detection With Image Distortion Analysis
Di Wen,Hu Han,Anil K. Jain +2 more
TL;DR: An efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA) that outperforms the state-of-the-art methods in spoof detection and highlights the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.
Journal ArticleDOI
50 years of biometric research
TL;DR: Unlocking the full potential of biometrics through inter-disciplinary research in the above areas will not only lead to widespread adoption of this promising technology, but will also result in wider user acceptance and societal impact.
Proceedings ArticleDOI
Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervision
TL;DR: This paper argues the importance of auxiliary supervision to guide the learning toward discriminative and generalizable cues, and introduces a new face anti-spoofing database that covers a large range of illumination, subject, and pose variations.
Journal ArticleDOI
Face Spoofing Detection Using Colour Texture Analysis
TL;DR: This paper introduces a novel and appealing approach for detecting face spoofing using a colour texture analysis that exploits the joint colour-texture information from the luminance and the chrominance channels by extracting complementary low-level feature descriptions from different colour spaces.
Journal ArticleDOI
Image Quality Assessment for Fake Biometric Detection: Application to Iris, Fingerprint, and Face Recognition
TL;DR: A novel software-based fake detection method that can be used in multiple biometric systems to detect different types of fraudulent access attempts and the experimental results show that the proposed method is highly competitive compared with other state-of-the-art approaches.
References
More filters
Journal ArticleDOI
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
TL;DR: A generalized gray-scale and rotation invariant operator presentation that allows for detecting the "uniform" patterns for any quantization of the angular space and for any spatial resolution and presents a method for combining multiple operators for multiresolution analysis.
Proceedings ArticleDOI
A face antispoofing database with diverse attacks
TL;DR: A face antispoofing database which covers a diverse range of potential attack variations, and a baseline algorithm is given for comparison, which explores the high frequency information in the facial region to determine the liveness.
Proceedings ArticleDOI
Face spoofing detection from single images using micro-texture analysis
TL;DR: This work presents a novel approach based on analyzing facial image textures for detecting whether there is a live person in front of the camera or a face print, and analyzes the texture of the facial images using multi-scale local binary patterns (LBP).
Proceedings ArticleDOI
Face detection with the modified census transform
TL;DR: An efficient four-stage classifier for rapid detection of illumination invariant local structure features for object detection and a modified census transform which enhances the original work of Zabih and Woodfill is proposed.
Book ChapterDOI
Face liveness detection from a single image with sparse low rank bilinear discriminative model
TL;DR: This paper develops two new extensions to the sparse logistic regression model which allow quick and accurate spoof detection and proposes two strategies to extract the essential information about different surface properties of a live human face or a photograph, in terms of latent samples.