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 TransformFace 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 ApproachIris 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 MachinesOther 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
