Wavelet-Local binary pattern based face recognition

@inproceedings{Ameen2017WaveletLocalBP,
  title={Wavelet-Local binary pattern based face recognition},
  author={Azad Abdullah Ameen and Hardi M. M-Saleh and Zrar Kh. Abdul},
  booktitle={BIOINFORMATICS 2017},
  year={2017}
}
Over the last twenty years face recognition has made immense progress based on statistical learning or subspace discriminant analysis. This paper investigates a technique to reduce features necessary for face recognition based on local binary pattern, which is constructed by applying wavelet transform into local binary pattern. The approach is evaluated in two ways: wavelet transform applied to the LBP features and wavelet transform applied twice on the original image and LBP features. The… 

Figures and Tables from this paper

A Survey on Unimodal, Multimodal Biometrics and Its Fusion Techniques
TLDR
The objective of this article is to analyze various methods of information fusion for biometrics, and to conclude with direction on future research proficiency in a multimodal biometric system using ECG, Fingerprint and Face features.

References

SHOWING 1-10 OF 15 REFERENCES
Boosting Local Binary Pattern (LBP)-Based Face Recognition
TLDR
This paper presents a novel approach for face recognition by boosting statistical local features based classifiers using AdaBoost algorithm to learn a similarity of every face image pairs.
Reducing the feature vector length in local binary pattern based face recognition
TLDR
Empirical studies on both human perception and LBP face recognition accuracy using the standard FERET database confirm that the concept of symmetry is an efficient discriminator.
Local binary pattern domain local appearance face recognition
TLDR
A fast face recognition algorithm that combines the discrete cosine transform based local appearance face recognition technique with the local binary pattern (LBP) representation of the face images to benefit from both the robust image representation capability of local binary patterns, and the compact representation capabilities of local appearance-based face recognition.
Face Recognition with Local Line Binary Pattern
In this paper, we introduce a novel face representation method for face recognition, called Local Line Binary Pattern (LLBP), which is motivated from Local Binary Pattern (LBP) due to it summarizes
Face Description with Local Binary Patterns: Application to Face Recognition
TLDR
This paper presents a novel and efficient facial image representation based on local binary pattern (LBP) texture features that is assessed in the face recognition problem under different challenges.
Facial expression recognition using log-Gabor filters and local binary pattern operators
TLDR
Two different methods of feature extraction for person-independent facial expression recognition from images are investigated, with comparable performance between Log-Gabor filters and LBP operator, with a classification accuracy of around 82.3% and 81.7% respectively.
Local Gabor Binary Pattern Whitened PCA: A Novel Approach for Face Recognition from Single Image Per Person
TLDR
A novel approach based on a combination of Gabor Filter, Local Binary Pattern and Whitened PCA (LGBPWP) is proposed, which has achieved the best results on the FERET database.
Face recognition by support vector machines
  • G. Guo, S. Li, K. Chan
  • Computer Science
    Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580)
  • 2000
TLDR
The potential of SVM on the Cambridge ORL face database, which consists of 400 images of 40 individuals, containing quite a high degree of variability in expression, pose, and facial details, is illustrated.
Introduction to Wavelets and Wavelet Transforms: A Primer
TLDR
This work describes the development of the Basic Multiresolution Wavelet System and some of its components, as well as some of the techniques used to design and implement these systems.
Learning to classify text using support vector machines - methods, theory and algorithms
  • T. Joachims
  • Computer Science
    The Kluwer international series in engineering and computer science
  • 2002
TLDR
This book gives a concise introduction to SVMs for pattern recognition, and it includes a detailed description of how to formulate text-classification tasks for machine learning.
...
...