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face anti-spoofing based on color texture analysis [article]

Zinelabidine Boulkenafet, Jukka Komulainen, Abdenour Hadid
2015 arXiv   pre-print
In this work, we propose a new face anti-spoofing method based on color texture analysis.  ...  Extensive experiments on two benchmark datasets, namely CASIA face anti-spoofing and Replay-Attack databases, showed excellent results compared to the state-of-the-art.  ...  Acknowledgments The financial support of the Academy of Finland is fully acknowledged.  ... 
arXiv:1511.06316v1 fatcat:ck6oskwmorfejm53vc4pxmccfu

A Survey on Face Anti-Spoofing Algorithms

Meigui Zhang, Kehui Zeng, Jinwei Wang
2020 Journal of Information Hiding and Privacy Protection  
This paper introduces the research progress of face anti-spoofing algorithm, and divides the existing face anti-spoofing methods into two categories: methods based on manual feature expression and methods  ...  How to design a face anti-spoofing method with high accuracy, strong generalization ability and meeting practical needs is the focus of current research.  ...  In view of this, Boulkenaf et al. [2] proposed a face anti-spoofing method based on color texture analysis.  ... 
doi:10.32604/jihpp.2020.010467 fatcat:5otomm6a3jcuxbhyorqq3ofgxi

Face Anti-Spoofing using Speeded-Up Robust Features and Fisher Vector Encoding

Zinelabidine Boulkenafet, Jukka Komulainen, Abdenour Hadid
2016 IEEE Signal Processing Letters  
The evaluation of our countermeasure on three challenging benchmark face spoofing databases, namely the CASIA Face Anti-Spoofing Database, the Replay-Attack Database and MSU Mobile Face Spoof Database,  ...  In this paper, we propose a novel solution based on describing the facial appearance by applying Fisher Vector encoding on Speeded-Up Robust Features (SURF) extracted from from different color spaces.  ...  In order to improve the generalization of texture based anti-spoofing methods, we have proposed the use of color texture analysis in [15] , exploiting the fact that the color gamut of printing and display  ... 
doi:10.1109/lsp.2016.2630740 fatcat:htgqq3iv4zbiphezcx4rufnody

Generalized face anti-spoofing by detecting pulse from face videos

Xiaobai Li, Jukka Komulainen, Guoying Zhao, Pong-Chi Yuen, Matti Pietikainen
2016 2016 23rd International Conference on Pattern Recognition (ICPR)  
Based on the fact that a pulse signal exists in a real living face but not in any mask or print material, the method could be a generalized solution for face liveness detection.  ...  Here we propose a robust anti-spoofing method by detecting pulse from face videos.  ...  ACKNOWLEDGMENT This work was sponsored by the Academy of Finland, Infotech Oulu and Tekes Fidipro program. This work was also partially supported by Hong Kong RGC General Research Fund HKBU 12201215.  ... 
doi:10.1109/icpr.2016.7900300 dblp:conf/icpr/LiKZYP16 fatcat:5py6nr32t5hz3lxppllitpiv3m

Fake Face Identification

Ms. Dilna E P1, Ms. Maneesha Manoj2, Ms. Jiji C J3, Ms. Jeena C J 4 Ms. Hrudhya K P5
2017 Zenodo  
We propose an efficient and rather robust face spoof detection algorithm based on Image Distortion Analysis (IDA).  ...  The proposed approach is extended to multi-frame face spoof detection in videos using a voting based scheme.  ...  CLASSIFICATION OF CAPTURED AND RECAPTURED IMAGES TO DETECT PHOTOGRAPH SPOOFING: A new face anti-spoofing approach, which is based on analysis of contrast and texture characteristics of captured and recaptured  ... 
doi:10.5281/zenodo.242479 fatcat:l6bbmde6wbccrc2kwmmqveltma

A Compact Deep Learning Model for Face Spoofing Detection [article]

Seyedkooshan Hashemifard, Mohammad Akbari
2021 arXiv   pre-print
The main idea is to take advantage of the strength of both methods to derive well-generalized solution for the problem.  ...  The procedure is done on different spoofing datasets such as ROSE-Youtu, SiW and NUAA Imposter datasets.  ...  The value of color texture descriptors for face anti-spoofing detection have been proved by retrospective studies. In this part our method is mostly based on [4] .  ... 
arXiv:2101.04756v1 fatcat:2ydd3jentrf5tca7nhmnle65l4

Hybrid Classification for Face Spoof Detection

Abhishek Mittal
2021 International Journal for Research in Applied Science and Engineering Technology  
Thus, GLCM (Grey Level Co-occurrence Matrix) is projected for analyzing the texture features in order to detect the face. The attendance of the query image is marked after detecting the face.  ...  Abstract: ML (machine learning) is consisted of a method of recognizing face. This technique is useful for the attendance system.  ...  There are mainly four categories of face anti-spoofing methods: (1) texture-based methods, (2) motion-based methods, (3) image quality-based methods, (4) depth-based methods.  ... 
doi:10.22214/ijraset.2021.39085 fatcat:wj5dy3up5jbezcehs24nw4bolu

Face anti-spoofing with joint spoofing medium detection and eye blinking analysis

2019 Computer Optics  
In this paper we present a novel CNN-based approach for face anti-spoofing, based on joint analysis of the presence of a spoofing medium and eye blinking.  ...  Existing face anti-spoofing methods are mostly based on texture analysis and due to lack of training data either use hand-crafted features or fine-tuned pretrained deep models.  ...  Texture analysis for face anti-spoofing Such methods are based on the assumption that real and fake faces images contain different texture patterns.  ... 
doi:10.18287/2412-6179-2019-43-4-618-626 fatcat:rz6xdlqixrfsvpan6fnd5abq5u

How far did we get in face spoofing detection?

Luiz Souza, Luciano Oliveira, Mauricio Pamplona, Joao Papa
2018 Engineering applications of artificial intelligence  
The growing use of control access systems based on face recognition shed light over the need for even more accurate systems to detect face spoofing attacks.  ...  In this paper, an extensive analysis on face spoofing detection works published in the last decade is presented.  ...  published a survey based on a chronological evolution of multimodal anti-spoofing methods.  ... 
doi:10.1016/j.engappai.2018.04.013 fatcat:j443aw2iozc3bncvapy5sarvde

Face Liveness Detection Based on Skin Blood Flow Analysis

Shun-Yi Wang, Shih-Hung Yang, Yon-Ping Chen, Jyun-We Huang
2017 Symmetry  
The second feature estimates the color distribution in the local regions of face images, instead of whole images, because image quality might be more discriminative in small areas of face images.  ...  The first feature obtains the texture difference between red and green channels of face images inspired by the observation that skin blood flow in the face has properties that enable distinction between  ...  Acknowledgments: This work was financially supported by the Ministry of Science and Technology of the  ... 
doi:10.3390/sym9120305 fatcat:nicxnoirgjbb5bvgq2qqozdlca

Spoof Face Detection Via Semi-Supervised Adversarial Training [article]

Chengwei Chen, Wang Yuan, Xuequan Lu, Lizhuang Ma
2020 arXiv   pre-print
Our approach is free of the spoof faces, thus being robust and general to different types of spoof, even unknown spoof.  ...  Face spoofing causes severe security threats in face recognition systems. Previous anti-spoofing works focused on supervised techniques, typically with either binary or auxiliary supervision.  ...  Feature-based Methods Most early face anti-spoofing works used handcrafted features of texture information for binary classification (e.g., SVM).  ... 
arXiv:2005.10999v1 fatcat:akn3bbfdgrczzdb476ym2ohiyy

Detection of Face Spoofing using Color Texture and Edge Features

2020 International journal of recent technology and engineering  
Traditional face spoofing detection techniques are not good enough as most of them focus only on the gray scale information and discarding the color information.  ...  Here a face spoofing detection approach with color texture and edge analysis is presented.  ...  It is based on the assumption that there is a difference in the texture of real faces and fake face. Texture analysis is widely used approach in the area of face spoofing detection.  ... 
doi:10.35940/ijrte.e1008.0285s20 fatcat:st2fmgl7yjcvrofbanbw2d5gqe

3D Face Anti-spoofing with Factorized Bilinear Coding [article]

Shan Jia, Xin Li, Chuanbo Hu, Guodong Guo, Zhengquan Xu
2020 arXiv   pre-print
In this work, we tackle the problem of detecting these realistic 3D face presentation attacks, and propose a novel anti-spoofing method from the perspective of fine-grained classification.  ...  Our method, based on factorized bilinear coding of multiple color channels (namely MC\_FBC), targets at learning subtle fine-grained differences between real and fake images.  ...  The proposed 3D face anti-spoofing method based on factorized bilinear coding is presented in Section IV.  ... 
arXiv:2005.06514v3 fatcat:whvinwbehfap5o4dtm5u54i2qa

Face Anti-Spoofing via Sample Learning Based Recurrent Neural Network (RNN)

Usman Muhammad, Tuomas Holmberg, Wheidima Carneiro de Melo, Abdenour Hadid
2019 British Machine Vision Conference  
Face biometric systems are vulnerable to spoofing attacks because of criminals who are developing different techniques such as print attack, replay attack, 3D mask attack, etc. to easily fool the face  ...  The proposed sample learning is based on sparse filtering which is applied for augmenting the features by leveraging Residual Networks (ResNet).  ...  Acknowledgment The financial support of the Academy of Finland is acknowledged.  ... 
dblp:conf/bmvc/MuhammadHMH19 fatcat:q6tlxtgc6jerrkc4ctuugmkwcm

A Cascade Face Spoofing Detector Based on Face Anti-Spoofing R-CNN and Improved Retinex LBP

Haonan Chen, Yaowu Chen, Xiang Tian, Rongxin Jiang
2019 IEEE Access  
In this paper, we design face anti-spoofing region-based convolutional neural network (FARCNN), based on improved Faster region-based convolutional neural network (R-CNN) framework.  ...  Besides, for the purpose of verifying the generalization capacity of the proposed cascade detector, we perform experiments on cross-databases and the results testify the effectiveness of our proposed method  ...  ACKNOWLEDGMENT The authors would like to thank the journal reviewers for their valuable suggestions.  ... 
doi:10.1109/access.2019.2955383 fatcat:vtlcihoqxnau3ernf66thvpncm
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