Издательство InTech, 2011, -326 pp.
Biometric recognition is one of the most widely studied problems in computer science. The use of biometrics techniques, such as face, fingerprints, iris, ears, is a solution for obtaining a secure personal identification. However, the old biometrics identification techniques are out of date.
The goal of this book is to provide the reader with the most up to date research performed in biometric recognition and to describe some novel methods of biometrics, emphasis on the state of the art skills.
The book consists of 15 chapters, each focusing on a most up to date issue. The chapters are divided into five sections- fingerprint recognition, face recognition, iris recognition, other biometrics and biometrics security. Section 1 collects five chapters on fingerprint recognition. Chapter 1 provides an effective fingerprint quality estimation approach in consideration of feature analysis for fingerprint quality estimation. In Chapter 2 the authors propose a novel hybrid shape and orientation descriptor that is designed for fingerprint matching. Chapter 3 gives a combined software-hardware approach to defeat fingerprint spoofing attack, and two methods are presented based on analyzing different optical properties by using optical coherence tomography (OCT) technology and the spectral analysis. In Chapter 4 the authors describe an optical information processing system for biometric authentication using the optical spatial-frequency correlation (OSC) system for the biometric authentication. Chapter 5 demonstrates that the concept of secondary fingerprint classification is feasible and consistent, and uses it to build an additional component into a fingerprint classification.
In the section 2 of face recognition, Chapter 6 gives a novel illumination normalization method simulating the performance of retina by combining two adaptive nonlinear functions, a difference of Gaussian filter and a truncation. In Chapter 7 the authors present a novel method of handling the variation caused by lip motion during speech by using temporal synchronization and normalization based on lip motion. Section 3 is a group of iris recognition articles, Chapter 8 presents an iris recognition system based on Local Binary Patte (LBP) features extraction and selection from multiple images, in which stable features are selected to describe the iris identity while the unreliable feature points are labeled in enrolment template. In Chapter 9 a comprehensive overview of the state-of-the-art in iris biometric cryptosystems is given. After discussing the fundamentals of iris recognition and biometric cryptosystems, existing key concepts are reviewed and implementations of different variations of iris-based fuzzy commitment are presented. Chapter 10 introduces an iris recognition method using the characteristics of orientation.
In the section of other biometrics, Gabor-Based Region covariance matrix (RCM) Features for Ear Recognition is proposed in Chapter
11. In Chapter 12 a fusion method for facial expression and gesture recognition to build a surveillance system by using Particle Swarm Optimization (PSO) and Cascaded SVMs (CSVM) classification is proposed. Chapter 13 examines the role and potential of Kansei and Kansei quality using Kansei engineering case studies, and introduces three case studies to improve Kansei quality in system design. In the last section of biometrics security, Chapter 14 deals with enhancing the efficiency of biometric by integrating it with salt value and encryption algorithms. In Chapter 15 the authors present a novel chaos-based biometrics template protection with secure authentication scheme.
Biometric recognition is one of the most widely studied problems in computer science. The use of biometrics techniques, such as face, fingerprints, iris, ears, is a solution for obtaining a secure personal identification. However, the old biometrics identification techniques are out of date.
The goal of this book is to provide the reader with the most up to date research performed in biometric recognition and to describe some novel methods of biometrics, emphasis on the state of the art skills.
The book consists of 15 chapters, each focusing on a most up to date issue. The chapters are divided into five sections- fingerprint recognition, face recognition, iris recognition, other biometrics and biometrics security. Section 1 collects five chapters on fingerprint recognition. Chapter 1 provides an effective fingerprint quality estimation approach in consideration of feature analysis for fingerprint quality estimation. In Chapter 2 the authors propose a novel hybrid shape and orientation descriptor that is designed for fingerprint matching. Chapter 3 gives a combined software-hardware approach to defeat fingerprint spoofing attack, and two methods are presented based on analyzing different optical properties by using optical coherence tomography (OCT) technology and the spectral analysis. In Chapter 4 the authors describe an optical information processing system for biometric authentication using the optical spatial-frequency correlation (OSC) system for the biometric authentication. Chapter 5 demonstrates that the concept of secondary fingerprint classification is feasible and consistent, and uses it to build an additional component into a fingerprint classification.
In the section 2 of face recognition, Chapter 6 gives a novel illumination normalization method simulating the performance of retina by combining two adaptive nonlinear functions, a difference of Gaussian filter and a truncation. In Chapter 7 the authors present a novel method of handling the variation caused by lip motion during speech by using temporal synchronization and normalization based on lip motion. Section 3 is a group of iris recognition articles, Chapter 8 presents an iris recognition system based on Local Binary Patte (LBP) features extraction and selection from multiple images, in which stable features are selected to describe the iris identity while the unreliable feature points are labeled in enrolment template. In Chapter 9 a comprehensive overview of the state-of-the-art in iris biometric cryptosystems is given. After discussing the fundamentals of iris recognition and biometric cryptosystems, existing key concepts are reviewed and implementations of different variations of iris-based fuzzy commitment are presented. Chapter 10 introduces an iris recognition method using the characteristics of orientation.
In the section of other biometrics, Gabor-Based Region covariance matrix (RCM) Features for Ear Recognition is proposed in Chapter
11. In Chapter 12 a fusion method for facial expression and gesture recognition to build a surveillance system by using Particle Swarm Optimization (PSO) and Cascaded SVMs (CSVM) classification is proposed. Chapter 13 examines the role and potential of Kansei and Kansei quality using Kansei engineering case studies, and introduces three case studies to improve Kansei quality in system design. In the last section of biometrics security, Chapter 14 deals with enhancing the efficiency of biometric by integrating it with salt value and encryption algorithms. In Chapter 15 the authors present a novel chaos-based biometrics template protection with secure authentication scheme.