Abstract
This paper presents a feature fusion based texture image classification method simultaneously using Gabor and Local Binary Patterns (LBP) feature. LBP and Gabor wavelets are two widely used two successful local image representation methods. This paper proposes two kinds of feature fusion methods, which perform in feature level and matching score level, respectively. We show that combining the two successful local image representations, i.e. Gabor wavelets and LBP, gives considerably better performance than either alone. Experiment results on MIT texture database demonstrate the effectiveness of our method.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/OJALA1/texclas.htm
Varma, M., Zisserman, A.: A Statistical Approach to Texture Classification from Single Images. International Journal of Computer Vision 62 (1-2), 61–81
Turk, M., Pentland, A.: Eigenfaces for recognition. J. Cognitive Neurosci. 3(1), 71–86 (1991)
Belhumeur, P.N., Hespanha, J.P., Kriegman, D.J.: Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection. IEEE Trans. Pattern Anal. Machine Intell. 19(7)
Yang, J., Zhang, D., Frangi, A.F., Yang, J.Y.: Two dimensional PCA: A new approach to appearance-based face representation and recognition. IEEE Trans. Pattern Anal. Machine Intell. 26(1), 131–137 (2004)
Yang, M., Zhang, L.: Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part VI. LNCS, vol. 6316, pp. 448–461. Springer, Heidelberg (2010)
Lee, T.S.: Image representation using 2D Gabor Wavelets. IEEE Transactions on PAMIÂ 18(10) (1996)
Ojala, T., Pietikainen, M., et al.: Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 971–987 (2002)
Ojala, T., Pietikainen, M., Harwood, D.: A comparative study of texture measures with classification based on featured distribution. Pattern Recognition 29(1), 51–59 (1996)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Du, Y. (2014). Texture Image Classification Using Gabor and LBP Feature. In: Pan, JS., Snasel, V., Corchado, E., Abraham, A., Wang, SL. (eds) Intelligent Data analysis and its Applications, Volume I. Advances in Intelligent Systems and Computing, vol 297. Springer, Cham. https://doi.org/10.1007/978-3-319-07776-5_35
Download citation
DOI: https://doi.org/10.1007/978-3-319-07776-5_35
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-07775-8
Online ISBN: 978-3-319-07776-5
eBook Packages: EngineeringEngineering (R0)