The fundamentals of unimodal palmprint authentication based on a biometric system: A review

Biometric system can be defined as the automated method of identifying or authenticating the identity of a living person based on physiological or behavioral traits. Palmprint biometric-based authentication has gained considerable attention in recent years. Globally, enterprises have been exploring biometric authorization for some time, for the purpose of security, payment processing, law enforcement CCTV systems, and even access to offices, buildings, and gyms via the entry doors. Palmprint biometric system can be divided into unimodal and multimodal. This paper will investigate the biometric system and provide a detailed overview of the palmprint technology with existing recognition approaches. Finally, we introduce a review of previous works based on a unimodal palmprint system using different databases

Multimodal Biometrics Enhancement Recognition System based on Fusion of Fingerprint and PalmPrint: A Review

This article is an overview of a current multimodal biometrics research based on fingerprint and palm-print. It explains the pervious study for each modal separately and its fusion technique with another biometric modal. The basic biometric system consists of four stages: firstly, the sensor which is used for enrolmen

Online palmprint identification

Author name used in this publication: Wai-Kin Kong2002-2003 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Multi-spectral palmprint recognition based on oriented multiscale log-Gabor filters

Among several palmprint recognition methods proposed recently, coding-based approaches using multi-spectral palmprint images are attractive owing to their high recognition rates. Aiming to further improve the performance of these approaches, this paper presents a novel multi-spectral palmprint recognition approach based on oriented multiscale log-Gabor filters. The proposed method aims to enhance the recognition performances by proposing novel solutions at three stages of the recognition process. Inspired by the bitwise competitive coding, the feature extraction employs a multi-resolution log-Gabor filtering where the final feature map is composed of the winning codes of the lowest filters’ bank response. The matching process employs a bitwise Hamming distance and Kullback–Leibler divergence as novel metrics to enable an efficient capture of the intra- and inter-similarities between palmprint feature maps. Finally, the decision stage is carried pout using a fusion of the scores generated from different spectral bands to reduce overlapping. In addition, a fusion of the feature maps through two proposed novel feature fusion techniques to allow us to eliminate the inherent redundancy of the features of neighboring spectral bands is also proposed. The experimental results obtained using the multi-spectral palmprint database MS-PolyU have shown that the proposed method achieves high accuracy in mono-spectral and multi-spectral recognition performances for both verification and identification modes; and also outperforms the state-of-the-art methods

A Review on Palm Print Recognition System

Biometrics based authentication and recognition system helps to identify individuals based on various behavior and physical characteristics, which can be used for their unique personal identifications. Various physical characteristics like iris patterns, facial features, fingerprint patterns, retina patterns, palmprint patterns etc. are utilized for such identification purposes, Palm print recognition is counted as most suitable and reliable biometric recognition system because of its merits, such as user friendliness, low cost, high accuracy and high speed. A system that uses palmprint as recognize individuals involves the matching of the various principal lines, creases and wrinkles on the palm surface. Since the random orientations of muscles and tissues of the hand create the palmprint patterns during birth, these patterns are unique so no two palmprint patterns are exactly same for any individuals. This paper provides a detailed overview of palmprint recognition approaches, by describing the various steps and processing involve in palmprint identification

Fast and efficient palmprint identification of a small sample within a full image.

In some fields like forensic research, experts demand that a found sample of an individual can be matched with its full counterpart contained in a database. The found sample may present several characteristics that make this matching more difficult to perform, such as distortion and, most importantly, a very small size. Several solutions have been presented intending to solve this problem, however, big computational effort is required or low recognition rate is obtained. In this paper, we present a fast, simple, and efficient method to relate a small sample of a partial palmprint to a full one using elemental optimization processes and a voting mechanic. Experimentation shows that our method performs with a higher recognition rate than the state of the art method, when trying to identify palmprint samples with a radius as small as 2.64 cm

Review of Multimodal Biometric Identification Using Hand Feature and Face

In the era of Information Technology, openness of the information is a major concern. As the confidentiality and integrity of the information is critically important, it has to be secured from unauthorized access. Security refers to prohibit some unauthorized persons from some important data or from some precious assets. So we need accurateness on automatic personal identification in various applications such as ATM, driving license, passports, citizen's card, cellular telephones, voter's ID card etc. Unimodal system carries some problems such as Noise in sensed data, Intra-class variations, Inter-class similarities, Non-universality and Spoof attacks. The accuracy of system is improved by combining different biometric traits which are called multimodal. This system gives more accuracy as it would be difficult for imposter to spoof multiple biometric traits simultaneously. This paper reviews different methods for fusion of biometric traits