Performance Analysis of Spiral Neighbourhood Topology Based Local Binary Patterns in Texture Recognition
DOI:
https://doi.org/10.18100/ijamec.270683Keywords:
Local binary patterns, texture recognition, feature extraction, classification methods, spiral topologyAbstract
In many texture recognition problems, Local Binary Patterns (LBP) method is used for feature extraction. This method is based on comparison of each centre pixel and its neighbours’ intensity value in image. Due to its simplicity of calculation, LBP has become one of the most popular feature extraction techniques. In literature, different neighbourhood topologies of LBP structure are given such as circle, square, ellipse, parabola, hyperbola, and Archimedean spiral. This paper focuses on the use of uniform and basic LBP that have spiral topology in texture classification. We first derive basic and uniform LBP features based on spiral topology. Then the performances of several classification methods such as linear discriminant analysis (LDA), linear regression classifier (LRC), support vector machines (SVM), Chi-square test, and G-test are compared using these features in UIUC texture database.Downloads
References
J. Raju ve C. Durai, A Survey on Texture Classification Techniques, Information Communication and Embedded Systems (ICICES), Chennai, 2013.
T. Ojala, M. Pietikainen ve D. Harwood, A Comparative Study of Texture Measures with Classification Based on Feature Distributions, Pattern Recognition, vol. 29, no. 1, pp. 51-59, 1996.
X. Huang, S. Li ve Y. Wang, Shape localization based on statistical method using extended local binary pattern, Proc.Int.Conf.Image Graph., 2004.
M. Heikkila, M. Pietikainen ve C. Schmid, Decription of interest regions with local binary patterns, Pattern Recognition, vol. 42, pp. 425-436, 2009.
S. C., Learning local binary patterns for gender classification on real-world face images, Pattern Recognition Letters, vol. 33, pp. 431-437, 2012.
M. G. K. Ong, T. Connie ve T. A. B. Jin, Touch-less palm print biometrics: Novel design and implementation, Image and Vision Computing, vol. 26, pp. 1551-1560, 2008.
B. Kir, M. Kurt ve O. Urhan, Local Binary Pattern Based Fast Digital Image Stabilization, IEEE Signal Processing Letters, vol. 22, pp. 341-345, 2015.
S.-M. Huang ve J.-F. Yang, Linear Discriminant Regression Classification for Face Recognition, IEEE Signal Processing Letters, vol. 20, no. 1, pp. 91-94, 2013.
Downloads
Published
Issue
Section
License
Copyright (c) 2016 International Journal of Applied Methods in Electronics and Computers
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
