TY  - JOUR
T1  - Performance Analysis of Local Binary Patterns in Texture Classification
AU - Sudha Sree, Ch. AU - Sekhara Rao, M.V.P. Chandra 
JO  - International Journal of System Signal Control and Engineering Application
VL  - 12
IS  - 4
SP  - 74
EP  - 84
PY  - 2019
DA  - 2001/08/19
SN  - 1997-5422
DO  - ijssceapp.2019.74.84
UR  - https://makhillpublications.co/view-article.php?doi=ijssceapp.2019.74.84
KW  - Local Binary Patten (LBP)
KW  -Local Ternary Pattern (LTP)
KW  -Completed Local Binary Pattern (CLBP)
KW  -Completed Local Binary Count (CLBC)
KW  -AdjacentEvaluation Completed Local Binary Pattern (AECLBP)
KW  -texture classification
KW  -rotation invariant
AB  - This study presents a detailed comparative
study on various Local Binary Pattern (LBP) variant
texture descriptors in texture classification. The work
includes nine various texture descriptor methods namely
LBPriu2, LBPri, LTP, VAR, LBP/VAR, CLBP, CLBC,
AECLBP, AELTP. The performance of these methods is
evaluated basing on three well-known benchmark texture
databases OUTEX, CUReT, UIUC, using the nearestneighbourhood
classifier.
ER  -