Internet and Mobile based Multimodal Biometric

Authentication and Monitoring System

(Including Voice, ECG, Ear and Palm Print)

Ear Palm print

Electrocardiogram (ECG)

Voice patterns

The objectives of the current project are as follows:

• Design and development of multimodal biometric

authentication and monitoring system on internet and

mobile platforms for both security and healthcare domains

• Combining the physiological, behavioral, internal

Objectives

• Combining the physiological, behavioral, internal

physiological and soft-biometric traits to improve the

performance of the biometric system for person or/and

patient authentication and monitoring services

• Products Development both in Security and Health domains

Multimodal Biometrics for Security and

Health Domains

Biometric systems automatically identify an individual and verify

the claimed identity of an individual based on their physiological

and/or behavioral characteristics.

The multimodal biometric system (MBS) employs two or more

biometric traits from the same individual in the authenticationbiometric traits from the same individual in the authentication

process.

The MBS commonly consists of five modules:

a) sensor module

b) feature extraction module

c) matching module

d) decision module

e) template module

Overall Multimodal Biometric System Architecture

FT: feature template, FM: fusion module, DM: decision module

Human individuals present different patterns in their ECG signals regarding waveshape, amplitude, interval, duration, due to the difference in the physicalconditions of the heart.

ECG Authentication Module

ECG

Acquisition

Filtering

(removal of

noises)

QRS

detection

ECG beat

segmentation

Beat selection

(similarity

measure)

feature

vector

Matching Module Feature Extraction Module

ECG fiducial

points

ECG beat

averaging

Period

normalization

ECG beat

pattern

vector

Classifier

Wavelet-based

similarity

measure

Fusion

&

Decision

Module

Database

Identity

(ID)

ECG Beat Correlations for Different Persons/Subjects

Figure: Correlation between adjacent beats (inter-beat correlation) in the ECG signals from different subjects.

Voice Authentication Module

Input

speech

Feature

Extraction

Ref. template or

model (speaker #1)

Similarity

Ref. template or

model (speaker #2)

SimilarityMaximum

selection

Identification

result

(Speaker ID)

Identification Process:

Ref. template or

model (speaker #N)

Similarity

Input

speech

Feature

Extraction

Verification

result

(Accept /Reject)

Similarity

Ref. template

or model

(speaker #M)

Input

speech

Decision

Threshold

Verification Process:

� Temporal features

• Low energy rate

• Zero crossing rate (ZCR)

• 4Hz modulation energy

• Pitch contour

� Spectral features

Features used for Voice Authentication

� Spectral features

• Spectral Centroid (sharpness)

• Spectral Flux (rate of change)

• Spectral Roll-Off (spectral shape)

• Spectral Flatness (deviation of the spectral form)

� Linear Predictive Cepstral Coefficients (LPCCs)

� Mel Frequency Cepstral Coefficients (MFCCs)

EAR and Palm Print Authentication Modules

Image Acquisition

Segmentation (Local Key

Points)

Feature Extraction

Preprocessing (noise removal)

feature vector

verifyResult

Registeror

Verify

SimilarityMatching

Decision

Database

register

registered models

Figure: Overview of Ear and Palm Print Authentication Systems

Ear and Palm print authentication module may use the

features:– Palm print geometry features such as principal lines,

wrinkles, ridge, atum points, minutiae points, hand geometry

– Ear shape features

– Principal component analysis (PCA) based features

– Log Gabor wavelets-based features

EAR and Palm Print Features for Authentication

– Log Gabor wavelets-based features

The proposed multimodal biometric system includes:

• Voice authentication module

• Electrocardiogram (ECG) authentication module

• Ear authentication module

• Palm print authentication module

• Fusion module

Technology and Benefits

Some of benefits are:

• Improve system accuracy and reliability

• Improve search efficiency

• Unique biometric profile

• Suitable for internet and mobile based healthcare services

• Healthcare services: patient authentication, and medical

records management

• Network security infrastructures: domain access, workstation,

data protection, remote access to resource, single sign-on,

application logon

• Personal data privacy: audio and video data, and document

• Secure electronic banking: debit and credit cards, investment

End Users

• Secure electronic banking: debit and credit cards, investment

funds and confidential financial transactions

• Consumer products: mobile-phone, home TV, washing

machine, refrigerator,

• Homecare services: physical access control, highly valued

property protections

• Academic Institutes: e-degree certificate, library access

• Travel services: e-passport, visa, and e-ticket