Line Scan Palmprint Recognition System

2017 ◽  
pp. 235-257 ◽  
Author(s):  
David Zhang ◽  
Guangming Lu ◽  
Lei Zhang
Keyword(s):  
Recognition System ◽  
Palmprint Recognition ◽  
Line Scan

scholarly journals Android Based Palmprint Recognition System

2014 ◽  
Vol 12 (1) ◽  
pp. 263 ◽  
Author(s):  
Gede Ngurah Pasek Pusia Putra ◽  
Ketut Gede Darma Putra ◽  
Putu Wira Buana
Keyword(s):  
Recognition System ◽  
Palmprint Recognition

Research and Evaluation of Multispectral Feature Selection and Fusion Model for Palmprint Recognition

2013 ◽  
Vol 411-414 ◽  
pp. 1291-1294
Author(s):  
Ying Xu ◽  
Fei Luo
Keyword(s):  
Bp Neural Network ◽  
Back Propagation ◽  
Recognition System ◽  
Singular Value ◽  
Personal Identification ◽  
Palmprint Recognition ◽  
Fusion Model ◽  
Network Method ◽  
Robust Recognition ◽  
Value Decomposition

Palmprint is widely used in personal identification for an accurate and robust recognition. Multispectral palmprint images capture under different illumination, including Red, Green, Blue and Infrared maybe contribute to the recognition results. However, the evaluation of selection and fusion of how this different spectral images can contribute to improve the robustness of the recognition system is imperative. In this paper, a novel wavelet-based multispectral fusion strategy is presented firstly to obtain the fused images; then block singular value decomposition (B-SVD) is applied for feature extraction; Finally back propagation (BP) neural network method is adopted for authentication. The proposed algorithm is evaluated on PolyU database which contains palmprint images from 500 individuals from four independent frequent band. The obtained results show robustness of our multispectral palmprint image fusion and selection model in comparison with the single spectral palmprint image that presented in the literature.

A Survey on Palmprint-Based Biometric Recognition System

2016 ◽  
pp. 304-326
Author(s):  
Y. L. Malathi Latha ◽  
Munaga V. N. K. Prasad
Keyword(s):  
Internal Surface ◽  
Recognition System ◽  
Palmprint Recognition ◽  
Behavioral Characteristics ◽  
Biometric Recognition ◽  
Palmprint Identification ◽  
Large Databases ◽  
Characteristic Features ◽  
Stable Characteristic ◽  
Review Current

The automatic use of physiological or behavioral characteristics to determine or verify identity of individual's is regarded as biometrics. Fingerprints, Iris, Voice, Face, and palmprints are considered as physiological biometrics whereas voice and signature are behavioral biometrics. Palmprint recognition is one of the popular methods which have been investigated over last fifteen years. Palmprint have very large internal surface and contain several unique stable characteristic features used to identify individuals. Several palmprint recognition methods have been extensively studied. This chapter is an attempt to review current palmprint research, describing image acquisition, preprocessing palmprint feature extraction and matching, palmprint related fusion and techniques used for real time palmprint identification in large databases. Various palmprint recognition methods are compared.

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