Abstract
In this paper, we prove that the Principal Component Analysis (PCA) and the Linear Discriminant Analysis (LDA) can be directly implemented in the DCT (Discrete Cosine Transform) domain and the results are exactly the same as the one obtained from the spatial domain. In some applications, compressed images are desirable to reduce the storage requirement. For images compressed using the DCT, e.g., in JPEG or MPEG standard, the PCA and LDA can be directly implemented in the DCT domain such that the inverse DCT transform can be skipped and the dimensionality of the original data can be initially reduced to cut down computational cost.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Fukunaga K (1990) Introduction to statistical pattern recognition, second edition. Academic Press
Rao K R, Yip P (1990) Discrete Cosine Transform: Algorithms, Advantages, Applications. Academic Press, Boston
Turk M A, Pentland A P, (1991) Eigen Faces for Recognition. Journal of cognitive Neuroscience. 3:71–86
Belhumeur P N, Hespanha J P, Kriegman D J, (1997) Eigenfaces Versus Fisher-faces: Recognition Using Class Specific Linear Projection. IEEE Trans. Pattern Analysis and Machine Intelligence. 19(7):711–720
Pan Z, Adams R, Bolouri H, (2000) Image Redundancy Reduction for Neural Network Classification Using Discrete Cosine Transforms. Proc. of The IEEE-INNS-ENNS International Joint Conf. on Neural Networks, Como, Italy. 3:149–154
Hafed Z M, Levine M D, (2001) Face Recognition Using the Discrete Cosine Transform. International Journal of Computer Vision. 43(3):167–188
Gonzalez R C, Woods R E, (1992) Digital Image Processing. Addison-Wesley
Yu H, Yang J, (2001) A Direct LDA Algorithm for High-dimensional Data-with Application to Face Recognition. Pattern Recognition. 34, 2067–2070.
Phillips P J, Wechsler H, Huang J, Rauss P, (1998) The FERET Database and Evaluation Procedure for Face Recognition Algorithms. Image and Vision Computing J. 16(5):295–306
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chen, W., Er, M.J., Wu, S. (2005). Fast PCA and LDA for JPEG Images. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_14
Download citation
DOI: https://doi.org/10.1007/3-540-32390-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25054-8
Online ISBN: 978-3-540-32390-7
eBook Packages: EngineeringEngineering (R0)