Abstract
The objective of the paper is face recognition using PCA and Bit plane slicing. It made a study on the dimensionality reduction on bit plane of images for face recognition. The proposed frame work would aid in robust design of face recognition system and addressed the challenging issues like pose and expression variation on ORL face database. It is in contrast to PCA on the image the design of PCA on bit plane reduces computation complexity and also reduces time. In the proposed frame work image is decomposed with the help of bit plane slicing, the feature have been extracted from the principle component analysis (PCA).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Patil AM, Kolhe SR, Patil PM (2009) Face recognition by PCA technique. In: Proceedings of the second international conference on emerging trends in engineering and technology, ICETET 2009, pp 192–195
Kokiopoulou E, Saad Y (2004) PCA and kernel PCA using polynomial filtering: a case study on face recognition
Meedeniya DA, Ratnaweera DAAC (2007) Enhanced face recognition through variation of principle component analysis (PCA). In: Second international conference on industrial and information systems, ICIIS 2007, pp 347–352
Kwang KI, Jung K, Kim HJ (2002) Face recognition using kernel principal component analysis. IEEE Signal Process Lett 9(2):40–42
Poon1 B, Ashraful Amin2 M, Yan H (2009) PCA based face recognition and testing criteria. In: Proceedings of the eighth international conference on machine learning and cybernetics, pp 2945–2949
AT&T Laboratories Cambridge, The Database of Faces, formerly ORL face database. Available at www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html
Sirovich L, Kirby M (1987) A low dimensional procedure for characterization of human faces. J Optical Soc Am A 4(3) 519–524
Punnam Chandar K, Mahesh Chandra M, Raman Kumar M, Swarna Latha B (2011) Preprocessing using SVD towards illumination invariant face recognition. In: Proceedings of IEEE RAICS 2011
Wu SQ, Wei LZ, Fang ZJ, Li RW, Ye XQ (2007) Infrared face recognition based on blood perfusion and sub-block DCT in wavelet domain. In: International conference on wavelet analysis and pattern recognition, vol 3, p 1252
Turk M, Pentland A (1991) Eigen faces for recognition. J Cognit Neurosci 3(1):71–86
Belhumeur PN, Hespanha JP, Kriegman DJ (1997) Eigenfaces versus fisherfaces: recognition using class specific linear projection. IEEE Trans Pattern Anal Mach Intell 19(7):711–720
Bartlett MS, Movellan JR, Sejnowski TJ (2002) Face recognition by independent component analysis. IEEE Trans Neural Netw 13(6):1450–1464
Moghaddam B, Nastar C, Pentland A (1996) A Bayesian similarity measure for direct measure for direct image matching. Proc Int Conf Pattern Recognit 2:350–358
Moghaddam B, Wahid W, Pentland A (1998) Beyond eigenfaces: Probabilistic matching for face recognition. In Proceedings of IEEE international conference on automatic face and gesture recognition, pp 30–35
Lanitis A, Taylor CJ, Cootes TF (1995) Automatic face identification system using flexible appearance models. Image Vis Comput 13(5):393–401
Shashua A, Riklin-Raviv T (2001) The quotient image: class-based rerendering and recognition with varying illuminations. IEEE Trans Pattern Anal Mach Intell 23(2):129–139
Zhang L, Samaras D (2003) Face recognition under variable lighting using harmonic image exemplars. In Proceedings of IEEE conference computer vision and pattern recognition, vol 1, pp 19–25
Chien J-T, Wu C–C (2002) Discriminant wavelet faces and nearest feature classifiers for face recognition. IEEE Trans Pattern Anal Mach Intell 24(12):1644–1649
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media New York
About this paper
Cite this paper
Srinivas, T., Sandeep Mohan, P., Shiva Shankar, R., Surender Reddy, C., Naganjaneyulu, P.V. (2013). Face Recognition Using PCA and Bit-Plane Slicing. In: Das, V. (eds) Proceedings of the Third International Conference on Trends in Information, Telecommunication and Computing. Lecture Notes in Electrical Engineering, vol 150. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3363-7_60
Download citation
DOI: https://doi.org/10.1007/978-1-4614-3363-7_60
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-3362-0
Online ISBN: 978-1-4614-3363-7
eBook Packages: EngineeringEngineering (R0)