Abstract
Face recognition in controlled environments is nowadays considered rather reliable, and if face is acquired in proper conditions, a good accuracy level can be achieved by state-of-the-art systems. However, we show that, even under these desirable conditions, some intentional or unintentional face image alterations can significantly affect the recognition performance. In particular, in scenarios where the user template is created from printed photographs rather than from images acquired live during enrollment (e.g., identity documents ), digital image alterations can severely affect the recognition results. In this chapter, we analyze both the effects of such alterations on face recognition algorithms and the human capabilities to deal with altered images.
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Sun, Y., Tistarelli, M., Maltoni, D.: Structural Similarity based image quality map for face recognition across plastic surgery. In: Proceedings of the IEEE Sixth International Conference on Biometrics: Theory, Applications and Systems (BTAS), pp. 1–8 (2013)
Ferrara, M., Franco, A., Maltoni, D., Sun, Y.: On the impact of alterations on face photo recognition accuracy. In: Proceedings of the International Conference on Image Analysis and Processing (ICIAP2013), Naples, pp. 743–751 (2013)
Ferrara, M., Franco, A., Maltoni, D.: The magic passport. In: Proceedings of the IEEE Int. Joint Conference on Biometrics (IJCB), Clearwater, Florida, pp. 1–7 (2014)
LiftMagic—Instant cosmetic surgery and anti-aging makeover tool [Online]. http://makeovr.com/liftmagic (2015, Jan)
White, D., Kemp, R.I., Jenkins, R., Matheson, M., Burton, A.M.: Passport officers’ errors in face matching. PLos ONE 9(8) (2014)
Clark, A., Bourlai, T.: Methodological insights on passport image enhancement. In: SPIE Newsroom: Defense & Security (2013)
Bourlai, T., Ross, A., Jain, A.K.: Restoring degraded face images for matching faxed or scanned photos. IEEE Trans. Inf. Forensics Secur. 6(2), 371–384 (2011)
Bourlai, T., Ross, A., Jain, A.K.: On matching digital face images against passport photos. In: IEEE International Conference on Biometrics, Identity and Security (2009)
Singh, R., et al.: Plastic surgery: a new dimension to face recognition. IEEE Trans. Inf. Forensics Secur. 5(3), 441–448 (2010)
Lakshmiprabha, N.S., Majumder, S.: Face recognition system invariant to plastic surgery. In: Proceedings of International Conference on Intelligent Systems Design and Applications, pp. 258–263 (2012)
Mun, M., Deorankar, A.: Implementation of plastic surgery face recognition using multimodal biometric features. Int. J. Comput. Sci. Inform. Technol. 5(3), 3711–3715 (2014)
Aggarwal, G., Biswas, S., Flynn, P.J., Bowyer, K.W.: A sparse representation approach to face matching across plastic surgery. In: Proceedings of IEEE workshop on the Applications of Computer Vision, pp. 113–119 (2012)
Bhatt, H.S., Bharadwaj, S., Singh, R., Vtsa, M., Noore, A.: Evolutionary granular approach for recognizing faces altered due to plastic surgery. In: Proceedings of IEEE Conference on Automatic Face and Gesture Recognition, pp. 720–725 (2011)
Bhatt, H.S., Bharadwaj, S., Singh, R., Vatsa, M.: Recognizing surgically altered face images using multiobjective evolutionary algorithm. IEEE Trans. Inf. Forensics Secur. 8(1), 89–100 (2013)
Liu, X., Shan, S., Chen, X.: Face recognition after plastic surgery: a comprehensive study. In: Proceedings of Asian Conference on Computer Vision, pp. 565–576 (2012)
Chude-Olisah, C.C., Sulong, G., Chude-Okonkwo, U.A.K., Hashim, S.Z.M.: Face recognition via edge-based Gabor feature representation for plastic surgery-altered images. EURASIP J. Adv. Sig. Process. (2014)
Ghatol, N.P., Paigude, R., Shirke, A.: Image morphing detection by locating tampered pixels with demosaicing algorithms. Int. J. Comput. Appl. 66(8), 23–26 (2013)
Wen, D., Han, H., Jain, A.K.: Face spoof detection with image distortion analysis. IEEE Trans. Inf. Forensics Secur. 10(4), 746–761 (2015)
Zhen, H., Lee, G., Lee, S.Y.: Integrating two-dimensional morphing and pose estimation for face recognition. J. Inf. Sci. Eng. 30, 257–272 (2014)
Padilha, A., Silva, J., Sebastiao, R.: Improving face recognition by video spatial morphing. In: Delac, K., Grgic, M. (eds.) Face Recognition (2007)
Zou, X., Kittler, J., Tena, J.: A morphing system for effective human face recognition. In: Proceedings of International Conference on Visual Information Engineering, pp. 215–220 (2008)
Kamgar-Parsi, B., Lawson, W., Kamgar-Parsi, B.: Toward development of a face recognition system for watchlist surveillance. IEEE Trans. Pattern Anal. Mach. Intell. 33(10), 1925–1937 (2011)
Chennamma, H.R., Rangarajan, L., Veerabhadrappa: Face identification from manipulated facial images using SIFT. In: Proceedings of 3rd International Conference on Emerging Trends in Engineering and Technology (ICETET), pp. 192–195 (2010)
Slama, C.: Manual of Photogrammetry, 4th edn. American Society of Photogrammetry, Falls Church, VA (1980)
Vass, G., Perlaki, T.: Applying and removing lens distortion in post production. In: Proceedings of 2nd Hungarian Conference on Computer Graphics and Geometry (2003)
Neurotechnology Inc.: Neurotechnology web site [Online]. http://www.neurotechnology.com/ (2015, Jan)
Luxand Inc.: Luxand web site [Online]. http://luxand.com (2015, Jan)
Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Bicego, M., Grosso, A., Tistarelli, M.: On the use of SIFT features for face authentication. In: Proceedings of Conference on Computer Vision and Pattern Recognition Workshop, p. 35 (2006)
Martinez, A.M., Benavente, R.: The AR face database. Computer Vision Center, CVC Technical Report (1998)
Maltoni, D., Maio, D., Jain, A.K., Prabhakar, S.: Handbook of Fingerprint Recognition, 2nd edn. Springer, New York, NJ, USA (2009)
FRONTEX: Research and Development Unit. Best Practice Technical Guidelines for Automated Border Control (ABC) Systems,—v2.0 (2012)
IATA: Airport with automated border control systems [Online]. http://www.iata.org/whatwedo/stb/maps/Pages/passenger-facilitation.aspx (2015, Jan)
Wikipedia: Morphing [Online]. http://en.wikipedia.org/wiki/Morphing (2015, Jan)
GIMP: GNU image manipulation program web site [Online]. http://www.gimp.org/ (2015, Jan)
GIMP: GIMP animation package [Online]. http://registry.gimp.org/node/18398 (2015, Jan)
ISO/IEC 19794-5, Information technology—biometric data interchange formats—part 5: face image data (2011)
FRONTEX: FRONTEX Web Site [Online]. http://frontex.europa.eu/ (2014, July)
Dorizzi, B., et al.: Fingerprint and on-line signature verification competitions at ICB 2009. In: Proceedings 3rd IAPR/IEEE International Conference on Biometrics (ICB09), Alghero (2009)
BioLab: FVC-onGoing web site [Online]. http://biolab.csr.unibo.it/fvcongoing (2015, Jan)
Phillips, P.J., Wechsler, H., Huang, J., Rauss, P.J.: The FERET database and evaluation procedure for face-recognition algorithms. Image Vision Comput. 16(5), 295–306 (1998)
Phillips, P.J., Moon, H., Rizvi, S.A., Rauss, P.J.: The FERET evaluation methodology for face-recognition algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 22(10), 1090–1104 (2000)
Eyedea Recognition Ltd.: Eyedea Recognition Web Site [Online]. http://www.eyedea.cz/ (2015, March)
Acknowledgment
The work leading to these results has received funding from the European Community’s Framework Programme (FP7/2007-2013) under grant agreement n° 284862.
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Ferrara, M., Franco, A., Maltoni, D. (2016). On the Effects of Image Alterations on Face Recognition Accuracy. In: Bourlai, T. (eds) Face Recognition Across the Imaging Spectrum. Springer, Cham. https://doi.org/10.1007/978-3-319-28501-6_9
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DOI: https://doi.org/10.1007/978-3-319-28501-6_9
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