کلمات کلیدی مربوط به کتاب سیستم های بیومتریک، طراحی و کاربردها: رشته های زیستی، روش های ریاضی و مدل سازی در زیست شناسی، بیومتریک
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Издательство InTech, 2011, -274 pp.
Biometric authentication has been
widely used for access control and security systems over the
past few years. It is the study of the physiological
(biometric) and behavioral (soft-biometric) traits of humans
which are required to classify them. A general biometric system
consists of different modules including single or multi-sensor
data acquisition, enrollment, feature extraction and
classification. A person can be identified on the basis of
different physiological traits like fingerprints, live scans,
faces, iris, hand geometry, gait, ear pattern and thermal
signature etc. Behavioral or soft-biometric attributes could be
helpful in classifying different persons however they have less
discrimination power as compared to biometric attributes. For
instance, facial expression recognition, height, gender etc.
The choice of a biometric feature can be made on the basis of
different factors like reliability, universality, uniqueness,
nonintrusiveness and its discrimination power depending upon
its application. Besides conventional applications of the
biometrics in security systems, access and documentation
control, different emerging applications of these systems have
been discussed in this book. These applications include Human
Robot Interaction (HRI), behavior in online learning and
medical applications like finding cholesterol level in iris
pattern. The purpose of this book is to provide the readers
with life cycle of different biometric authentication systems
from their design and development to qualification and final
application. The major systems discussed in this book include
fingerprint identification, face recognition, iris segmentation
and classification, signature verification and other
miscellaneous systems which describe management policies of
biometrics, reliability measures, pressure based typing and
signature verification, bio-chemical systems and behavioral
characteristics.
Over the past few years, a major part of the revenue collected
from the biometric industry is obtained from fingerprint
identification systems and Automatic Fingerprint Identification
Systems (AFIS) due to their reliability, collectability and
application in document classification (e.g. biometric
passports and identity cards). Section I provides details about
the development of fingerprint identification and verification
system and a new approach called finger-vein recognition which
studies the vein patterns in the fingers. Finger-vein
identification system has immunity to counterfeit, active
liveliness, user friendliness and permanence over the
conventional fingerprints identification systems. Fingerprints
are easy to spoof however current approaches like liveliness
detection and finger-vein pattern identification can easily
cope with such challenges. Moreover, reliability measure of
fingerprint systems using Weibull approach is described in
detail.
Human faces are preferred over the other biometric systems due
to their non-intrusive nature and applications at different
public places for biometric and soft-biometric classification.
Section II of the book describes detailed study on the
segmentation, recognition and modeling of the human faces. A
stand-alone system for 3D human face modeling from a single
image has been developed in detail. This system is applied to
HRI applications. The model parameters from a single face image
contain identity, facial expressions, gender, age and ethnical
information of the person and therefore can be applied to
different public places for interactive applications.
Moreover face identification in images and videos is studied
using transform domains which include subspace learning methods
like PCA, ICA and LDA and transforms like wavelet and cosine
transforms. The features extracted from these methods are
comparatively studied by using different standard classifiers.
A novel approach towards face segmentation in cluttered
backgrounds has also been described which provides an image
descriptor based on self-similarities which captures the
general structure of an image.
Current iris patterns recognition systems are reliable but
collectability is the major challenge for them. A thorough
study along with design and development of iris recognition
systems has been provided in section III of this book. Image
segmentation, normalization, feature extraction and
classification stages are studied in detail. Besides
conventional iris recognition systems, this section provides
medical application to find presence of cholesterol level in
iris pattern.
Finally, the last section of the book provides different
biometric and soft-biometric systems. This provides management
policies of the biometric systems, signature verification,
pressure based system which uses signature and keyboard typing,
behavior analysis of simultaneous singing and piano playing
application for students of different categories and design of
a portable biometric system that can measure the amount of
absorption of the visible collimated beam that passes by the
sample to know the absorbance of the sample.
In summary, this book provides the students and the researchers
with different approaches to develop biometric authentication
systems and at the same time provides state-of-the-art
approaches in their design and development. The approaches have
been thoroughly tested on standard databases and in real world
applications.
Fingerprints Verification and
Identification
Reliability of Fingerprint Biometry (Weibull Approach)
Finger-Vein Recognition Based on Gabor Features
Efficient Fingerprint Recognition Through Improvement of
Feature Level Clustering, Indexing and Matching Using Discrete
Cosine Transform
Face
Recognition
Facial Identification Based on Transform Domains for Images and
Videos
Towards Unconstrained Face Recognition Using 3D Face
Model
Digital Signature: A Novel Adaptative Image Segmentation
Approach
Iris Segmentation and
Identification
Solutions for Iris Segmentation
Detecting Cholesterol Presence with Iris Recognition
Algorithm
Robust Feature Extraction and Iris Recognition for Biometric
Personal Identification
Iris Recognition System Using Support Vector Machines
Other
Biometrics
Verification of the Effectiveness of Blended Learning in
Teaching Performance Skills for Simultaneous Singing and Piano
Playing
Portable Biometric System of High Sensitivity Absorption
Detection
Texture Analysis for Off-Line Signature Verification
Design and Evaluation of a Pressure Based Typing Biometric
Authentication System