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Non-overlapped blockwise interpolated local binary pattern as periocular feature

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Abstract

Most of the prominent features of human face are present in the ocular area, referred as the periocular region. Complex and dense features in these regions makes it a candidate to be used as a biometric trait. This paper discusses an effective method for periocular recognition using non-overlapped blockwise interpolated local binary pattern (iLBP) features. For a given periocular image, an iLBP coded feature image is obtained and further divided into four equal non-overlapping sub-regions. From each sub-region having iLBP pattern, eight bin histogram features are calculated. A single feature vector is formed by concatenating blocked histograms of each non-overlapping region. Binned histogram based feature is also extracted using Phase Intensive Global Pattern (PIGP) features for comparison of results. Experiments are conducted on UBIRIS.v1 and UBIPr.v2 datasets. From the experiments, it is observed that selected histogram feature bins through the proposed approach provide a more compact representation of periocular image and size of the feature vector is also reduced with significant improvement in performance.

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Abbreviations

LBP:

Local Binary Pattern

iLBP:

Interpolated Local Binary Pattern

PIGP:

Phase Intensive Global Pattern

PILP:

Phase Intensive Local Pattern

R-PILP:

Reduced Phase Intensive Local Pattern

DLBP:

Dominant Local Binary Pattern

ULBP:

Uniform Local Binary Pattern

MB-LBP:

Multi-block Local Binary Pattern

uMLBP:

uniform Multiscale Local Binary Pattern

H-3P-LBP:

Hierarchical Three-patch Local Binary Pattern

DCT:

Discrete Cosine Transform

DFT:

Discrete Fourier Transform

DWT:

Discrete Wavelet Transform

WLBP:

Walsh-Hadamard Local Binary Pattern

CNN:

Convolution Neural Network

HOG:

Histogram of Oriented Gradient

GE:

Genetic & Evolutionary

GO:

Gradient Orientation

MLBP:

Multiresolution Local Binary Pattern

TERELM:

Total Error Rate Minimization

LoG:

Laplacian of Gaussian

ISV:

Inter-Session Variability

WLD:

Weber Local Descriptor

LPQ:

Local Phase Quantization

LTP:

Local Ternary Pattern

NILBP:

Intensity based Local Binary Pattern

LSP:

Local Salient Pattern

LDA:

Linear Discriminant Analysis

NIR:

Near Infrared Rays

VW:

Visible Wavelength

FAR:

False Acceptance Rate

FRR:

False Rejection Rate

ROC:

Receiver Operating Characteristic

EER:

Equal Error Rate

CISP:

Compact Image Set Representation

MDA:

Multiple Discriminant Analysis

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Acknowledgments

This research is partially supported by the following projects:

(1) Grant No. ETI/359/2014 by Fund for Improvement of S&T Infrastructure in Universities and Higher Educational Institutions (FIST) Program 2016, Department of Science and Technology, Government of India.

(2) Information Security Education & Awareness Project (Phase II), Ministry of Electronics and Information Technology (MeitY), Government of India.

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  1. Department of Computer Science and Engineering, National Institute of Technology Rourkela, Odisha, 769 008, India

    Gautam Kumar, Sambit Bakshi, Pankaj Kumar Sa & Banshidhar Majhi

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Kumar, G., Bakshi, S., Sa, P.K. et al. Non-overlapped blockwise interpolated local binary pattern as periocular feature. Multimed Tools Appl 80, 16565–16597 (2021). https://doi.org/10.1007/s11042-020-08708-w

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