Weitere Kapitel dieses Buchs durch Wischen aufrufen
Passwords are normally used for authentication in systems. They have several drawbacks like passwords can be guessed easily, they can be copied. Since biometric authentication is excelling in every field whether it be banking sector, corporate sector, etc., they are considered quite secure and mostly preferred for authentication. But every system has some flaws; therefore biometric authentication can be attacked so as to obtain any confidential information. One of them is face authentication system. Face is a unique characteristic that can be used to authenticate a person. Face authentication systems can be easily spoofed by using Replay and Printed paper attacks. Spoofing means real person’s identity is copied and used for harming any type of data. In this review paper, mainly LBP (Local Binary Pattern) descriptor is used, which is considered especially for texture analysis. LBP descriptor divides the captured face into blocks and calculates histogram for each block. Thus each block histograms are concatenated and finally are combined together. The formed histogram of whole face is compared with other face histograms and the similarity between the faces is found out. Spoof faces will not have similar histograms like the real face. And this helps in detecting Spoof face. Different spoof face detection methods are discussed in this review paper. Detection of spoof face is done by considering Moiré patterns, image distortion analysis algorithm. This review paper aims at securing confidential information by providing face unlock mechanism wherein spoof faces are to be detected.
Bitte loggen Sie sich ein, um Zugang zu diesem Inhalt zu erhalten
Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:
K. Jain, “Secure Face Unlock: Spoof Detection on Smartphones,” in IEEE Transactions on Information Forensics and Security, vol. 11, no. 10, pp. 2268–2283, Oct. 2016.
A. K. Singh, P. Joshi and G. C. Nandi, “Face recognition with liveness detection using eye and mouth movement,” 2014 International Conference on Signal Propagation and Computer Technology (ICSPCT 2014), Ajmer, 2014, pp. 592–597.
S. Tirunagari, N. Poh, D. Windridge, A. Iorliam, N. Suki and A. T. S. Ho, “Detection of Face Spoofing Using Visual Dynamics,” in IEEE Transactions on Information Forensics and Security, vol. 10, no. 4, pp. 762–777, April 2015.
W. Kim, S. Suh and J. J. Han, “Face Liveness Detection From a Single Image via Diffusion Speed Model,” in IEEE Transactions on Image Processing, vol. 24, no. 8, pp. 2456 2465, Aug. 2015.
Z. Boulkenafet, J. Komulainen and A. Hadid, “Face anti-spoofing based on color texture analysis,” 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, 2015, pp. 2636–2640.
Z. Boulkenafet, J. Komulainen, Xiaoyi Feng and A. Hadid, “Scale space texture analysis for face anti-spoofing,” 2016 International Conference on Biometrics (ICB), Halmstad, 2016, pp. 1–6.
D. C. Garcia and R. L. de Queiroz, “Face-Spoofing 2D-Detection Based on Moiré-Pattern Analysis,” in IEEE Transactions on Information Forensics and Security, vol. 10, no. 4, pp. 778–786, April 2015.
Q. T. Phan, D. T. Dang-Nguyen, G. Boato and F. G. B. De Natale, “FACE spoofing detection using LDP-TOP,” 2016 IEEE International Conference on Image Processing (ICIP), Phoenix, AZ, 2016, pp. 404–408.
A. Agarwal, R. Singh and M. Vatsa, “Face anti-spoofing using Haralick features,” 2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS), Niagara Falls, NY, 2016, pp. 1–6.
K. Patel, H. Han, A. K. Jain, and G. Ott, “Live face video vs. spoof face video: Use of moir´e patterns to detect replay video attacks,” in Proc.ICB, 2015, pp. 1–8.
D. Wen, H. Han and A. K. Jain, “Face Spoof Detection With Image Distortion Analysis,” in IEEE Transactions on Information Forensics and Security, vol. 10, no. 4, pp. 746–761, April 2015.
- A Review Spoof Face Recognition Using LBP Descriptor
- Springer Singapore
Neuer Inhalt/© ITandMEDIA, Best Practices für die Mitarbeiter-Partizipation in der Produktentwicklung/© astrosystem | stock.adobe.com