Palmprint recognition using 2d-gabor wavelet based sparse coding and RBPNN classifier

Authors:
Li Shang;Wenjun Huai;Guiping Dai;Jie Chen;Jixiang Du
Affiliations:
Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;Department of Electronic Information Engineering, Suzhou Vocational University, Suzhou, Jiangsu, China;Department of Computer Science and Technology, Huaqiao University, Quanzhou, Fujian, China
Venue:
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part II
Year:
2010

Citing 5
Cited 0

Sparse code shrinkage: denoising of nongaussian data by maximum likelihood estimation

Neural Computation
Image Feature Extraction by Sparse Coding and Independent Component Analysis

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 2 - Volume 2
Non-negative Matrix Factorization with Sparseness Constraints

The Journal of Machine Learning Research
Denoising Natural Images Using Sparse Coding Algorithm Based on the Kurtosis Measurement

ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks, Part II
Image reconstruction using NMF with sparse constraints based on kurtosis measurement criterion

ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposed a novel and successful method for recognizing palmprint using 2D-Gabor wavelet filter based sparse coding (SC) algorithm and the radial basis probabilistic neural network (RBPNN) classifier proposed by us Features of Palmprint images are extracted by this SC algorithm, which exploits feature coefficients' Kurtosis as the maximum sparse measure criterion and a variance term of sparse coefficients as the fixed information capacity At the same time, in order to reduce the iteration time, features of 2D-Gabor wavelet filter are also used as the initialization feature matrix The RBPNN classifier is trained by the orthogonal least square (OLS) algorithm and its structure is optimized by the recursive OLS algorithm (ROLSA) Experimental results show that this SC algorithm is successful in extracting features of palmprint images, and the RBPNN model achieves higher recognition rate and better classification efficiency with other usual classifiers.