The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.
A Completed Modeling of Local Binary Pattern Operator for Texture Classification
Abstract
In this correspondence, a completed modeling of the local binary pattern (LBP) operator is proposed and an associated completed LBP (CLBP) scheme is developed for texture classification. A local region is represented by its center pixel and a local difference sign-magnitude transform (LDSMT). The center pixels represent the image gray level and they are converted into a binary code, namely CLBP-Center (CLBP_C), by global thresholding. LDSMT decomposes the image local differences into two complementary components: the signs and the magnitudes, and two operators, namely CLBP-Sign (CLBP_S) and CLBP-Magnitude (CLBP_M), are proposed to code them. The traditional LBP is equivalent to the CLBP_S part of CLBP, and we show that CLBP_S preserves more information of the local structure than CLBP_M, which explains why the simple LBP operator can extract the texture features reasonably well. By combining CLBP_S, CLBP_M, and CLBP_C features into joint or hybrid distributions, significant improvement can be made for rotation invariant texture classification.
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Cites
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Face Description with Local Binary Patterns: Application to Face Recognition
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Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions
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Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions
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Song, K., & Yan, Y. (2013) · Applied Surface Science · doi:10.1016/j.apsusc.2013.09.002 · Cited by 1,026
Handcrafted vs. non-handcrafted features for computer vision classification
Nanni, L., Ghidoni, S., & Brahnam, S. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2017.05.025 · Cited by 542
Local binary features for texture classification: Taxonomy and experimental study
Liu, L., Fieguth, P., Guo, Y., Wang, X., & Pietikäinen, M. (2017) · Pattern Recognition · doi:10.1016/j.patcog.2016.08.032 · Cited by 369
Presentation Attack Detection Methods for Face Recognition Systems: A Comprehensive Survey
Ramachandra, R., & Busch, C. (2018) · ACM Computing Surveys · doi:10.1145/3038924 · Cited by 332
Facial Expression Recognition: A Survey
Huang, Y., Chen, F., Lv, S., & Wang, X. (2019) · Symmetry · doi:10.3390/sym11101189 · Cited by 195
Metadata
- Authors
- Guo, Z., Zhang, L., & Zhang, D.
- Venue
- IEEE Transactions on Image Processing
- Published
- 2010-06
- Volume
- 19
- Issue
- 6
- Pages
- 1657-1663
- ISSN
- 1057-7149 (ISSN-L)
- 1941-0042
- OpenAlex
- W2147141800
- Cited by
- 2,115
- References
- 26
- FWCI
- 77.03
- Type
- journal article
- Language
- en
- Open access
- closed
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