Weisheng Li
ABSTRACT
As the traditional LBP algorithm only considers the single threshold characteristics without using the relationship between the threshold and the neighbor pixels, the useful characteristics will be lost. In this paper a method of face recognition based on Dynamic Threshold Local Binary Pattern (DTLBP) is proposed. In DTLBP the binary digit is encoded with a dynamic threshold, which is adjusted by the relationship of neighborhood pixels gray value and the central pixel gray value. The DTLBP method, proposed by this paper, uses dynamic threshold to encode, and computes the statistic histogram referring to the work in LBP method. Finally, the experimental results based on Yale B, CMU PIE and ORL face databases show that the method is superior to the traditional LBP and LTP method.
- Tan, X. and Triggs, B. 2010. Enhanced local texture feature sets for face recognition under difficult lighting conditions. IEEE Trans on Image Processing. 19, 6 (Jun. 2010), 1635--1650. Google Scholar
Digital Library
- Zhao, W., Chellappa, R. and Rosenfeld, A. 2003. Face recognition: A literature survey. ACM Computing Surveys. 35, 4 (Dec. 2003), 399--458. Google ScholarDigital Library
- Adani, Y. and Ullman, S. 1994. Face recognition: the problem of compensating for the illumination direction. In Prceedings of ECCV Conference. 19, 7(Jul, 1994), 162--187.Google Scholar
- Ojala, T., Valkealahti, K., Oja, E. and Pietikainen, M. 2001. Texture discrimination with multi-dimensional distributions of signed gray level differences. Patt. Recogn. 34, (2001), 727--739.Google Scholar
- Ojala, T., Pietikainen, M. and Maenpaa, T. 2002. Multiresolution gray-scale and rotation-invariant texture classification with local binary patterns. IEEE Trans. Patt. Anal. Mach. Intell. 24, 7 (Jul, 2002), 971--987. Google ScholarDigital Library
- Kyong, I., Chang, Kevin, W., Bowyer, Patrick Flynn, J. 2003. Face Recognition Using 2D and 3DFacialData. Workshop in Multimodal User Authentication. (Dec. 2003), 25--32.Google Scholar
- Jian-gang, W., Eng, T. L., Xiang, C. and Ronda, V. 2007. Real-time Stereo Face Recognition by Fusing Appearance and Depth Fisherfaces. Signal Processing. 49, 3 (2007), 409--423. Google ScholarDigital Library
- Heng-xin, C., Tang, Y. Y. and Bin, F. 2011. A Multi-Layer Contrast Analysis Method for Texture Classification Based on LBP. Pattern Recognition and Artificial Intelligence. 25, 1 (Jan, 2011), 1--9.Google Scholar
- Chi-Ho Chan, Josef Kittler. and Kieron Messer. 2007. Multi-scale Local Binary Pattern Histograms for Face Recognition. Lecture Notes in Computer Science. 46, 42 (2007), 809--818. Google ScholarDigital Library
- Ahonen, T., Hadid, A., Pietikainen, M. 2004. Face recognition with local binary patterns. In Proceedings of European Conference on Computer Vision. Prague 30, 21 (2004), 469--481.Google ScholarCross Ref
- Ahonen, T., Hadid, A. and Pietikainen, M. 2006. Face description with local binary patterns: Application to face recognition. IEEE Trans. Pattern Anal. Mach. Intell. 28, 12 (Dec, 2006), 2037--2041. Google ScholarDigital Library
- Georghiades, A. S., Belhumeur, P. N. and Kriegman, D. J. 2001. From few to many: Illumination cone models for face recognition under variable lighting and pose. IEEE Trans. Pattern Anal. Mach. Intell. 23, 6 (Jun, 2001), 643--660. Google ScholarDigital Library
- Sim, T., Baker, S. and Bsat, M. 2002. The CMU pose, illumination, and expression (PIE) database. In Proc. IEEE Int. Conf. Automatic Face and Gesture Recognition. (2002), 46--51. Google ScholarDigital Library
- http://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html. ORL face database.Google Scholar
Index Terms
- Face recognition method based on dynamic threshold local binary pattern
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