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Author Li Liu ♦ Yunli Long ♦ Fieguth, P.W. ♦ Songyang Lao ♦ Guoying Zhao
Sponsorship IEEE Signal Processing Society
Source IEEE Xplore Digital Library
Content type Text
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
File Format PDF
Copyright Year ©1992
Language English
Subject Domain (in DDC) Natural sciences & mathematics ♦ Physics ♦ Electricity & electronics
Subject Keyword Noise ♦ Feature extraction ♦ Robustness ♦ Histograms ♦ Educational institutions ♦ Vectors ♦ Lighting ♦ texture analysis ♦ Texture descriptors ♦ rotation invariance ♦ local binary pattern (LBP) ♦ feature extraction
Abstract In this paper, we propose a simple, efficient, yet robust multiresolution approach to texture classification-binary rotation invariant and noise tolerant (BRINT). The proposed approach is very fast to build, very compact while remaining robust to illumination variations, rotation changes, and noise. We develop a novel and simple strategy to compute a local binary descriptor based on the conventional local binary pattern (LBP) approach, preserving the advantageous characteristics of uniform LBP. Points are sampled in a circular neighborhood, but keeping the number of bins in a single-scale LBP histogram constant and small, such that arbitrarily large circular neighborhoods can be sampled and compactly encoded over a number of scales. There is no necessity to learn a texton dictionary, as in methods based on clustering, and no tuning of parameters is required to deal with different data sets. Extensive experimental results on representative texture databases show that the proposed BRINT not only demonstrates superior performance to a number of recent state-of-the-art LBP variants under normal conditions, but also performs significantly and consistently better in presence of noise due to its high distinctiveness and robustness. This noise robustness characteristic of the proposed BRINT is evaluated quantitatively with different artificially generated types and levels of noise (including Gaussian, salt and pepper, and speckle noise) in natural texture images.
Description Author affiliation :: Dept. of Comput. Sci. & Eng., Univ. of Oulu, Oulu, Finland
Author affiliation :: Dept. of Syst. Design Eng., Univ. of Waterloo, Waterloo, ON, Canada
Author affiliation :: Sch. of Electron. Sci. & Eng., Nat. Univ. of Defense Technol., Changsha, China
Author affiliation :: Sch. of Inf. Syst. & Manage., Nat. Univ. of Defense Technol., Changsha, China
ISSN 10577149
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-01-01
Publisher Place U.S.A.
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Volume Number 23
Issue Number 7
Size (in Bytes) 6.01 MB
Page Count 14
Starting Page 3071
Ending Page 3084

Source: IEEE Xplore Digital Library