Abstract
In this paper, the merits of the Local Binary Patterns (LBP) representation are investigated in the context of face recognition using long-wave infrared images. Long-wave infrared images are invariant to illumination, but at the same time they are affected by a fixed-pattern noise inherent to this technology. The fixed-pattern is normally compensated by means of a non-uniformity correction method. Our study shows that the LBP approach is robust to the fixed-pattern noise, as well as to the presence of glasses. Not only no noise suppressing preprocessing is needed, but in fact if a non-uniformity correction method is applied, the image texture is amplified and the performance of the LBP degraded.
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Keywords
- Face Recognition
- Local Binary Pattern
- Focal Plane Array
- Local Binary Pattern Operator
- Linear Discriminant Analysis Method
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References
Zou, X., Kittler, J., Messer, K.: Illumination Invariant Face Recognition: A Survey. In: First IEEE International Conference on Biometrics: Theory, Applications, and Systems, pp. 1–8 (2007)
Zou, X., Kittler, J., Messer, K.: Face recognition using active near-ir illumination. In: British Machine Vision Conference Proceedings (2005)
Li, S.Z., Chu, R., Liao, S., Zhang, L.: Illumination invariant face recognition using near-infrared images. IEEE Trans. Pattern Anal. Mach. Intell. 29(4), 627–639 (2007)
Socolinsky, D.A., Wolff, L.B., Neuheisel, J.D., Eveland, C.K.: Illimination invariant face recognition using thermal infrared imagery. In: Proc. IEEE CS Conf. Comp. Vision and Pattern recognition, vol. 1, pp. 527–534 (2001)
Kong, S.G., Heo, J., Abidi, B.R., Ki Paik, J., Abidi, M.A.: Recent advances in visual and infrared face recognition - a review. Computer Vision and Image Undertanding 97(1), 103–135 (2005)
Heo, J., Savvides, M., Vijaya Kumar, V.K.: Performance Evaluation of Face Recognition using visual and thermal imagery with advanced correlation filters. In: Conference on Computer Vision and Pattern Recognition, pp. 9–14. IEEE Computer Society, Los Alamitos (2005)
Socolinsky, D.A., Selinger, A.: A Comparative Analysis of Face Recognition Performance with Visible and Thermal Infrared Imagery. In: ICPR 2002: Proceedings of the 16Th International Conference on Pattern Recognition, vol. 4(4) (2002)
Bebis, G., Gyaourova, A., Singh, A., Pavlidis, I.: Face recognition by fusing thermal infrared and visible imagery. Image and Vision Computing 24(7), 727–742 (2006)
Singh, R., Vatsa, M., Noore, A.: Integrated multilevel image fusion and match score fusion of visible and infrared face images for robust face recognition. Pattern Recogn. 41(3), 880–893 (2008)
Chen, X., Flynn, P.J., Bowyer, K.w.: PCA-based face recognition in infrared imagery: baseline and comparative studies. In: IEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG, pp. 127–134 (2003)
Pron, H., Menanteau, W., Bissieux, C., Beaudoin, J.L.: Characterization of a focal plane array (FPA) infrared camera. Quantitativa Infrared Thermography QIRT Open Archives, QIRT, 2000–2061 (2000), http://qirt.gel.ulaval.ca
Milton, A., Barone, F., Kruer, M.: Influence of nonuniformity on infrared focal plane array performance. Opctical Engineering 24, 855–862 (1985)
Hardie, R., Hayat, M., Armstrong, E., Yasuda, B.: Scene-based nonuniformity correction using video sequences and registration. Applied Optics 39, 1241–1250 (2000)
Ratliff, B., Hayat, M., Tyo, J.: Generalized algebraic scene-based nonuniformity correction algorihtm. The JOSA-A Opt. Soc. of America 22, 239–249 (2005)
Harris, J., Chiang, Y.: Nonuniformity correction of infrared image sequences using constant statistics constraint. IEEE Trans. on Image Processing 8, 1148–1151 (1999)
Pezoa, J., Hayat, M., Torres, S., Rahman, M.: Multimodel kalman filtering for adaptive nonuniformity correction in infrared sensors. The JOSA-A Opt. Soc. of America 23, 1282–1291 (2006)
Averbuch, A., Liron, G., Bobrovsky, B.Z.: Scene based non-uniformity correction in thermal images using Kalman filter. Image and Vision Computing 25, 833–851 (2007)
San Martin, C., Meza, P., Torres, S., Carrillo, R.: Improved Infrared Face Identification Performance Using Nonuniformity Correction Techniques. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds.) ACIVS 2008. LNCS, vol. 5259, pp. 1115–1123. Springer, Heidelberg (2008)
Ahonen, T., Hadid, A., Pietikäinen, M.: Face recognition with local binary patterns. In: Pajdla, T., Matas, J. (eds.) ECCV 2004. LNCS, vol. 3021, pp. 469–481. Springer, Heidelberg (2004)
Marcel, S., Rodriguez, Y., Heusch, G.: On the Recent Use of Local Binary Patterns for Face Authentication. International Journal on Image and Video Processing Special Issue on Facial Image Processing (2007)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell. 7(19), 711–720 (1997)
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Méndez, H., Martín, C.S., Kittler, J., Plasencia, Y., García-Reyes, E. (2009). Face Recognition with LWIR Imagery Using Local Binary Patterns. In: Tistarelli, M., Nixon, M.S. (eds) Advances in Biometrics. ICB 2009. Lecture Notes in Computer Science, vol 5558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01793-3_34
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DOI: https://doi.org/10.1007/978-3-642-01793-3_34
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