Multi-scale logarithmic difference face recognition based on local binary pattern
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@Article{JICS-12-041,
author = {Lifang Lin and Chuanlin Zhang},
title = {Multi-scale logarithmic difference face recognition based on local binary pattern},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {12},
number = {1},
pages = {041--051},
abstract = {In order to solve the problem that face recognition is sensitive to illumination variation and local
binary pattern has small spatial support region. A novel face recognition approach which is multi-scale
logarithmic difference face recognition based on local binary pattern is proposed. Firstly, LBP operator is
used to extract the texture feature of the face. Secondly, the LBP feature is used to extract the light invariant
based on the Lambertian reflection model. Then, the light invariant is used to obtain the multi-scale features
according to the different distances, and the refined feature-map is obtained by the linear combination of
multi-scale features. Finally, face recognition is performed using refined feature-map. Extension experiments
on four data sets (Yale, FERET, ORL and MUI PIE) show that the proposed method which compares to LBP,
MSLDE and Gradientface in different illumination conditions can improve the recognition performance.
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22497.html}
}
TY - JOUR
T1 - Multi-scale logarithmic difference face recognition based on local binary pattern
AU - Lifang Lin and Chuanlin Zhang
JO - Journal of Information and Computing Science
VL - 1
SP - 041
EP - 051
PY - 2024
DA - 2024/01
SN - 12
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22497.html
KW - Local binary pattern (LBP)
KW - feature extract
KW - face recognition
KW - multiple scales
KW - logarithm
transform
KW - difference.
AB - In order to solve the problem that face recognition is sensitive to illumination variation and local
binary pattern has small spatial support region. A novel face recognition approach which is multi-scale
logarithmic difference face recognition based on local binary pattern is proposed. Firstly, LBP operator is
used to extract the texture feature of the face. Secondly, the LBP feature is used to extract the light invariant
based on the Lambertian reflection model. Then, the light invariant is used to obtain the multi-scale features
according to the different distances, and the refined feature-map is obtained by the linear combination of
multi-scale features. Finally, face recognition is performed using refined feature-map. Extension experiments
on four data sets (Yale, FERET, ORL and MUI PIE) show that the proposed method which compares to LBP,
MSLDE and Gradientface in different illumination conditions can improve the recognition performance.
Lifang Lin and Chuanlin Zhang. (2024). Multi-scale logarithmic difference face recognition based on local binary pattern.
Journal of Information and Computing Science. 12 (1).
041-051.
doi:
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